An Introduction to Cognitive Psychology: Processes and Disorders [3rd ed.] 9781848720916

Table of contents :
1. Introduction to Cognitive Psychology
2. Perception
3. Attention
4. Disorders of Perception and Attention
5 Short-Term Memory
6. Long-Term Memory
7. Disorders of Memory
8. Thinking and Problem-Solving
9. Disorders of Thinking and Problem-Solving
10. Language
11. Disorders of Language
12. Cognition and Emotion
Glossary
References

Citation preview

An Introduction to Cognitive Psychology An Introduction to Cognitive Psychology: Processes and disorders is a comprehensive introductory textbook for undergraduate students. The third edition of this well-established text has been completely revised and updated to cover all the key areas of cognition, including perception, attention, memory, thinking and language. Uniquely, alongside chapters on normal cognitive function, there are chapters on related clinical disorders (agnosia, amnesia, thought disorder and aphasia) which help to provide a thorough insight into the nature of cognition. Key features: r
Completely revised and updated throughout to provide a comprehensive overview of current thinking in the field r
Accessibly written and including new authors, including Sophie Scott, Tom Manly, Hayley Ness and Elizabeth Styles, all established experts in their field r
A new chapter on emotion and cognition, written by Michael Eysenck, the leading authority in the field r
Greater coverage of neuropsychological disorders, with additional material from the latest brain imaging research that has completely revolutionized neuropsychology r
Specially designed textbook features, chapter summaries, further reading and a glossary of key terms r
A companion website featuring an extensive range of online resources for both teachers and students. An Introduction to Cognitive Psychology is written to cover all levels of ability and includes numerous figures and illustrations to assist learning. The book has sufficient depth to appeal to the most able students, while the clear and accessible writing style will help students who find the material difficult. It will appeal to all undergraduate students of psychology, and also medical students and those studying in related clinical professions such as nursing. David Groome was formerly Principal Lecturer and Senior Academic in Psychology at the University of Westminster, where he worked from 1970 to 2011. He retired from teaching in August 2011 but continues to carry out research and write books. His research interests include cognition and memory, and their relationship with clinical disorders. He has published a number of research papers on these topics and is the co-author of four previous textbooks.

Advance praise for the new edition of An Introduction to Cognitive Psychology: ‘A highly useful text which helpfully explains the associated disorders in all the key subject areas of cognitive psychology.’ – Parveen Bhatarah, School of Psychology, London Metropolitan University, UK ‘An Introduction to Cognitive Psychology comprehensively and exhaustively covers the basics and main topics of cognitive psychology. The authors are all experts in their research areas, and the overall content of the book is informative, up-to-date and clearly structured.’ – Wolfgang Minker, Institute of Communications Engineering, Ulm University, Germany ‘This book is a highly readable introduction to the major figures and studies in cognitive research. The visuals and summaries included throughout will help students process and understand all of the important information, whilst also provoking discussions surrounding controversial issues in psychology and learning.’ – Rosalind Horowitz, College of Education and Human Development, The University of Texas at San Antonio, USA ‘Any student wishing to understand basic principles in cognition alongside disorderly behaviour will find this a useful alternative to other introductory cognitive textbooks on the market today. The divergence in basic cognitive function will capture student attention while providing them with a solid foundation.’ – Karla A. Lassonde, Minnesota State University, Mankato, USA ‘I am very impressed with the distinctive approach taken to cognitive psychology in this textbook, where each topic is explored through the lenses of behavioral research, computer models, clinical neuropsychology and neuroscience. I appreciate the effort that the authors make to integrate neuroscience and neuropsychology, with intriguing case studies and the coverage of disorders skillfully integrated with the rest of the text.’ – Erik Nilsen, Department of Psychology, Lewis and Clark College, USA ‘An Introduction to Cognitive Psychology provides an up-to-date, topical and accessible overview of this core area of psychology. The coverage of topics is extensive and there is an excellent balance of theory, research and application in the treatment of each area. Three aspects of this text stand out: the multiauthor approach that provides a variety of perspectives from a range of experts; a strong consideration of disorders in cognition, an important, often ignored, aspect of the discipline of great interest to students; and finally, the chapter on cognition and emotion, an important topic rarely covered in texts of this type, is a welcome addition.’ – John Reece, School of Health Sciences, RMIT University, Australia ‘With a unique blend of cognition and clinical (neuro)psychology, this book integrates a comprehensive introduction to the core areas of experimental cognitive psychology with a nuanced review of the cognitive aspects of clinical disorders. The clinical discussion avoids unhelpful syndrome pigeon-holing, and brings alive a topic that many students can find a bit dry.’ – Ullrich Ecker, The University of Western Australia, Australia ‘This new edition has been updated throughout to include the latest cutting-edge research. Its refreshing approach combines both neuropsychology and cognitive psychology in alternating chapters making it relevant to students of cognitive psychology, neuropsychology or medicine. The book is clearly organized and accessible despite the enormous breadth that it covers.’ – Michael D. Patterson, Nanyang Technological University, Singapore ‘This is a very comprehensive introduction to cognitive psychology with a particular focus on disorders of cognition. The book provides an integrated approach to illustrate how the human mind works through introductions to both normal and disordered cognitive functions. A wide range of topics with different approaches, including experimental and computational modelling approaches, alongside the inclusion of materials from cognitive neuroscience and neuropsychology, will enhance students’ understanding of how the brain gives rise to the mind.’ – Janet H. Hsiao, Department of Psychology, University of Hong Kong, Hong Kong

AN INTRODUCTION TO Cognitive Psychology Processes and disorders Third Edition David Groome With Nicola Brace, Graham Edgar, Helen Edgar, Michael Eysenck, Tom Manly, Hayley Ness, Graham Pike, Sophie Scott and Elizabeth Styles

Third edition published 2014 by Psychology Press 27 Church Road, Hove, East Sussex BN3 2FA and by Psychology Press 711 Third Avenue, New York, NY 10017 Psychology Press is an imprint of the Taylor & Francis Group, an informa business © 2014 David Groome, Nicola Brace, Graham Edgar, Helen Edgar, Michael Eysenck, Tom Manly, Hayley Ness, Graham Pike, Sophie Scott, Elizabeth Styles The right of David Groome, Nicola Brace, Graham Edgar, Helen Edgar, Michael Eysenck, Tom Manly, Hayley Ness, Graham Pike, Sophie Scott, and Elizabeth Styles to be identified as author of this work has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. First edition published by Psychology Press 1999 Second edition published by Psychology Press 2006 British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging in Publication Data A catalog record for this book has been requested ISBN: 978-1-84872-091-6 (hbk) ISBN: 978-1-84872-092-3 (pbk) ISBN: 978-1-315-87155-4 (ebk) Typeset in Sabon by Book Now Ltd, London

Contents List of illustrations Authors Preface Acknowledgements 1. INTRODUCTION TO COGNITIVE PSYCHOLOGY David Groome 1.1 Cognitive processes A definition of cognitive psychology Stages of cognitive processing Approaches to the study of cognition 1.2 Experimental cognitive psychology The first cognitive psychologists The rise and fall of behaviourism Gestalt and schema theories Top-down and bottom-up processing 1.3 Computer models of information processing Computer analogies and computer modelling of brain functions Feature detectors The limited-capacity processor model 1.4 Cognitive neuroscience and neuropsychology The structure and function of the brain Information storage in the brain 1.5 Automatic processing Automatic versus controlled processing Conscious awareness 1.6 Minds, brains and computers Integrating the main approaches to cognition Summary Further reading 2. PERCEPTION Graham Edgar, Helen Edgar and Graham Pike 2.1 Introduction 2.2 Visual perception Theories of perception – schemas and template matching The Gestalt approach Feature-extraction theories Marr’s computational theory

xiv xxi xxiii xxiv 2 3 3 3 4 6 6 6 7 9 10 10 10 12 12 12 15 17 17 19 22 22 22 23 24 25 25 25 27 28 29

vi

Contents Biederman’s recognition-by-components approach Parallel distributed processing approaches Visual illusions The difference between sensation and perception ‘Looked but failed to see’ (LBFS) accidents The influence of top-down processing: an example The constructivist approach: perception for recognition Evidence for the constructivist approach: masking and re-entrant processing The Gibsonian view of perception: perception for action Evidence for the Gibsonian approach The structure of the visual system The dorsal and ventral streams The interaction of the dorsal and ventral streams: perception for recognition and action 2.3 Auditory perception Auditory localisation Auditory attention Interactions and real-world examples Top-down influences on auditory perception 2.4 Haptic perception More than five senses? Proprioception, kinesthesis and haptic information Using illusions to explore haptic information Applications of haptic information to driving 2.5 Conclusion Summary Further reading 3. ATTENTION Elizabeth Styles 3.1 What is attention? 3.2 What is attention for? 3.3 Where is the limit? The search for the bottleneck 3.4 The problem of breakthrough 3.5 Subliminal priming effects 3.6 Object selection, inhibition and negative priming 3.7 Directing the spotlight of visual attention 3.8 Cross-modal cueing of attention 3.9 Visual search 3.10 Evidence for and against FIT 3.11 The importance of task differences 3.12 Attention, working memory and distraction 3.13 Attention and cognitive control 3.14 Combining tasks 3.15 Practice, automaticity and skill Summary Further reading

30 30 31 36 37 40 41 43 45 45 46 46 48 50 51 55 55 56 58 58 60 62 66 67 68 69 70 71 72 74 75 76 77 78 80 82 83 85 86 87 90 92 96 97

Contents 4. DISORDERS OF PERCEPTION AND ATTENTION Tom Manly and Hayley Ness 4.1 Introduction 4.2 Synaesthesia The nature of synaesthesia Incidence and familiarity Experimental investigations of synaesthesia Brain-imaging studies of synaesthesia Mechanisms underlying synaesthesia Synaesthesia – advantage or disadvantage? Conclusions 4.3 Blindsight Blindsight – a sceptical perspective The sensation of blindsight The implications of blindsight: one visual system or two? 4.4 Unilateral spatial neglect A disorder of attention? Do we all show neglect? Rehabilitation for unilateral spatial neglect Explaining unilateral spatial neglect 4.5 Visual agnosia Apperceptive and associative agnosia Form and integrative agnosia Living with visual agnosia Perception and action Comparing form and integrative agnosia Recognising living and non-living objects 4.6 Disorders of face processing Living with prosopagnosia What kind of damage causes acquired prosopagnosia? Prosopagnosia – a face-specific disorder? Covert recognition in prosopagnosia Can prosopagnosia occur without brain damage? Types of impairment in developmental and congenital prosopagnosia Summary Further reading 5 SHORT-TERM MEMORY David Groome 5.1 Multistore models of memory The dual-store theory of memory Clinical evidence for the STM/LTM distinction The recency effect 5.2 Measuring STM performance The duration of STM storage STM capacity

98 99 100 102 103 104 105 107 108 108 109 110 112 112 113 114 117 117 118 119 119 120 120 123 124 124 126 126 127 129 131 132 133 134 135 136 137 137 138 139 140 140 141

vii

viii

Contents 5.3 The working memory model Working memory 5.4 The phonological loop Evidence for the phonological loop The word-length effect Sub-components of the phonological loop Non-speech sounds The phonological loop and language acquisition 5.5 The visuo-spatial sketchpad Measuring the capacity of the visuo-spatial sketchpad Evidence for the visuo-spatial sketchpad Sub-components of the visuo-spatial sketchpad 5.6 The central executive Investigating the central executive Impairment of central executive function 5.7 Working memory theory today The episodic buffer Unitary theories of memory Controlled attention theory Individual differences in WM Neuro-imaging studies and WM Summary Further reading 6. LONG-TERM MEMORY David Groome 6.1 The nature and function of memory Memory and its importance in everyday life Encoding, storage and retrieval of memory 6.2 The first memory experiments Ebbinghaus and the forgetting curve Interference and decay 6.3 Meaning, knowledge and schemas Bartlett’s story recall experiments and the schema theory The effect of meaning and knowledge on memory Schemas and scripts Schemas and distortion Meaning and mnemonics 6.4 Input processing and encoding Levels of processing theory Orienting tasks Levels theory revised Elaborative and maintenance rehearsal Elaborative encoding and organisation 6.5 Retrieval and retrieval cues Recall and recognition Generate and recognise theory Cue-dependent forgetting and the encoding specificity principle

142 142 143 143 144 144 145 146 146 146 147 148 149 149 149 150 150 151 151 151 153 154 155 156 157 157 157 158 158 159 160 160 162 164 164 165 166 166 166 168 169 169 170 170 171 171

Contents Transfer-appropriate processing Context-dependent memory State-dependent and mood-dependent memory 6.6 Memory systems Episodic and semantic memory Familiarity and recollection The R & K (‘remember and know’) procedure Implicit and explicit memory Implicit memory in everyday life Processes underlying different memory systems 6.7 Retrieval practice and retrieval inhibition Retrieval practice and the testing effect Decay with disuse Retrieval-induced forgetting (RIF) RIF in real-life settings Retrieval inhibition, disuse and psychiatric disorders Directed forgetting Reconsolidation 6.8 Memory in everyday life Ecological validity Autobiographical memory Flashbulb memories Eyewitness testimony The cognitive interview Summary Further reading 7. DISORDERS OF MEMORY David Groome 7.1 Amnesia and its causes The effects of amnesia Causes of amnesia Amnesia as an impairment of long-term memory 7.2 Anterograde and retrograde amnesia Distinguishing anterograde from retrograde amnesia Testing anterograde and retrograde amnesia Anterograde and retrograde impairment in organic amnesia Focal retrograde and focal anterograde amnesia Explaining the temporal gradient in retrograde amnesia Brain lesions associated with anterograde and retrograde amnesia 7.3 Intact and impaired memory systems Motor skills Implicit memory Familiarity and context recollection Episodic and semantic memory Explaining preserved memory function in amnesia

173 174 176 177 177 179 181 181 183 185 185 185 186 187 188 189 190 191 192 192 193 196 197 200 202 203 204 205 205 205 208 210 210 211 212 213 215 215 218 219 220 221 223 225

ix

x

Contents 7.4 Theories of amnesia Encoding deficit theories of amnesia Retrieval deficit theories of amnesia Separate impairments of encoding and retrieval The standard model of consolidation Multiple trace theory Impaired declarative memory Impaired binding Impaired perceptual processing 7.5 Other types of memory disorder Impairment of short-term memory Concussion amnesia ECT and memory loss Frontal lobe lesions Memory loss in the normal elderly Psychogenic amnesia 7.6 Rehabilitation Helping patients to cope with amnesia Maximising memory performance External memory aids Summary Further reading 8. THINKING AND PROBLEM-SOLVING Nicola Brace 8.1 Introduction 8.2 Early research on problem-solving The Gestalt approach to problem-solving 8.3 The information-processing approach to problem-solving Problem-solving strategies Difficulties in applying problem-solving strategies Problem representation 8.4 Problem-solving by analogy Are analogies spontaneously used to solve problems? Comparing experts and novices Encouraging the use of analogies to solve problems 8.5 Deductive and inductive reasoning Inductive reasoning: hypothesis generation Is confirmation bias a general tendency? Deductive reasoning Wason’s four-card selection task 8.6 Theoretical approaches to reasoning Mental logic theories Pragmatic reasoning schemata Mental models The probabilistic approach Dual-process accounts Summary Further reading

226 226 227 227 228 228 229 229 230 230 230 231 232 233 234 235 236 236 236 237 238 239 240 241 242 242 245 245 247 249 251 253 254 256 257 258 259 261 263 264 264 265 266 268 269 270 271

Contents 9. DISORDERS OF THINKING AND PROBLEM-SOLVING Nicola Brace 9.1 Introduction 9.2 Anatomy and physiology of the frontal lobes 9.3 The impact of frontal lobe damage on behaviour Early clinical studies Early animal studies Later clinical studies and the effect on ‘executive’ functions 9.4 Impairments in the deployment of attention Sustaining and concentrating attention Suppressing attention 9.5 Impairments in abstract and conceptual thinking Sorting tasks Evidence concerning perseveration Going beyond perseveration 9.6 Impaired strategy formation Cognitive estimation tasks Goal-oriented problem-solving 9.7 Deficits in everyday higher-order planning 9.8 Conceptual issues Supervisory attentional system Alternative approaches Fractionation of the executive functions of the frontal lobes Diversity and unity of executive functions A final note Summary Further reading 10. LANGUAGE Sophie Scott 10.1 Introduction 10.2 The language system Speech sounds Visual languages – British Sign Language Words and morphemes Sentence level The level of discourse 10.3 Psychology and linguistics Tasks in the study of language 10.4 Recognising spoken and written words How do we recognise spoken words? How do we recognise written words? Morphemes and word recognition Database approaches 10.5 Understanding the meanings of words

272 273 274 275 275 276 277 279 279 279 281 281 283 284 286 286 288 289 293 293 295 296 298 299 299 300 302 303 303 304 306 307 308 309 309 311 311 311 314 316 316 317

xi

xii

Contents 10.6 Explaining lexical access in language comprehension How should we model linguistic processing – rules or regularities? The case of regular and irregular past-tense verbs 10.7 Sentence comprehension 10.8 Language production 10.9 Discourse level Coordinating conversations Meaning and intention in conversation Social conversations Note Summary Further reading 11. DISORDERS OF LANGUAGE Sophie Scott 11.1 Introduction 11.2 Models of aphasia The Wernicke–Lichtheim model of aphasia and its modifications The Boston Aphasia Classification System 11.3 Detailed symptoms of aphasic profiles Broca’s aphasia Wernicke’s aphasia Conduction aphasia Global aphasia Transcortical motor aphasia Transcortical sensory aphasia (TSA) Mixed transcortical aphasia (isolation aphasia) Anomic aphasia Pure word deafness Phonagnosia Dysarthria Speech apraxia Prosody production and perception 11.4 Psychological and psycholinguistic aspects of aphasia Phonetic deficits Syntactic deficits Semantic deficits 11.5 Functional imaging of human language processing Speech perception A study of speech perception using PET The neural basis of context effects in speech perception Rehearsing non-words versus listening to non-words Neural basis of speech production 11.6 Reading Visual word recognition Neural control of eye movements Routes to reading

318

320 323 326 330 330 331 332 333 334 334 337 337 339 339 341 346 346 347 348 348 349 349 349 349 349 350 350 351 351 351 352 352 352 353 353 353 356 356 357 358 358 359 361

Contents Surface dyslexia Phonological dyslexia Deep dyslexia Functional-imaging studies of written language 11.7 Developmental disorders of language Developmental disorders of speech perception and production – specific language impairment Developmental disorders of reading – dyslexia Developmental disorders of speech production Disorders of language use in autism Summary Further reading 12. COGNITION AND EMOTION Michael Eysenck 12.1 Introduction Manipulating mood states 12.2 Mood and attention Attentional narrowing Attention and memory 12.3 Mood and memory Mood manipulations and memory Flashbulb memories Recovered memories Amygdala Urbach–Wiethe disease Summary and conclusions 12.4 Judgement and decision-making: mood effects Anxiety Sadness Anger Positive mood Summary and conclusions Limitations 12.5 Judgement and decision-making: cognitive neuroscience Cognitive neuroscience research Limitations 12.6 Reasoning Working memory Summary Further reading Glossary References Author index Subject index

361 362 362 364 365 365 366 367 368 368 369 370 371 372 372 372 373 374 375 377 377 379 380 380 380 381 384 385 387 390 391 391 393 394 395 395 396 397 398 407 453 460

xiii

Illustrations FIGURES 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 1.10 1.11 1.12 1.13 1.14 1.15 1.16 1.17 1.18 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 2.10 2.11

2.12 2.13 2.14

The main stages of cognitive processing The four main approaches to studying cognitive psychology An MRI scanner William James A rat learning to run through a maze A shape recognised by most observers Schemas generated for comparison with new input Top-down and bottom-up processing Wiring to a simple feature detector Wiring to a complex feature detector Broadbent’s model of selective attention A side view of the human brain, showing the main lobes Neurons and their connecting synapses A cell assembly A demonstration of automatic processing Driving a car involves many automatic responses for an experienced driver The supervisory attention system model Does your dog have conscious awareness? And is he wondering the same about you? ‘But, Grandmother, what big teeth you’ve got’ Stimuli of the kind used by Shepard and Metzler (1971) A reversible figure Examples of Gestalt laws of perceptual organisation Pandemonium The Hermann grid The Müller-Lyer illusion A possible explanation for the Müller-Lyer illusion The Ames room When size constancy breaks down The avenue and court (strewn with brightly coloured ornaments) carefully constructed by the male bowerbird to woo the female ‘Well I never expected that!’ The components of perception High sensory conspicuity does not guarantee accurate perception. . .

3 4 5 6 7 8 8 9 11 11 12 13 16 16 18 18 19 21 26 26 27 28 29 32 32 33 34 34

35 36 37 37

Illustrations 2.15 2.16

2.17 2.18 2.19 2.20 2.21 2.22 2.23 2.24 2.25 2.26 2.27 2.28 2.29 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9

3.10 3.11 4.1 4.2 4.3 4.4 4.5

The effect of contrast on detectability Vehicles that had earlier been carrying members of a BBC TV team, hit by ‘friendly fire’ from an aircraft in the 2003 Iraq war What do you see? The faces of Einstein Demonstrating what we really see as opposed to what we feel we see A target and mask of the type used by Enns and Di Lollo (2000) What do you do with this? The dorsal and ventral streams Sound localisation in the horizontal plane Motion parallax How many senses do we have? A (CGI) recreation of the task from the Gallace and Spence (2005) study The Ebbinghaus illusion A (CGI) recreation of the task from the Westwood and Goodale (2003) study Answer to Figure 2.17 Would you hear your name spoken from across a crowded room? Everyday tasks like shopping demand attention The Stroop test A simplified version of Broadbent’s filter model Schematic faces similar to those used by Friesen and Kingstone (1998) The ventriloquist effect Stimuli of the type used by Navon (1977) Examples of the kind of stimuli used in feature integration tasks A simplified explanation of how Norman and Shallice’s (1986) model explains automatic behaviour and behaviour controlled by the SAS in the Stroop task Multitasking The power law of practice Baron-Cohen’s investigation of EP’s synaesthesia Weiskrantz’s investigation of DB’s blindsight Examples of drawings of clock faces produced by patients with unilateral visual neglect The attempts of a patient with apperceptive agnosia to copy six simple figures HJA’s definition of the word ‘carrot’ and his attempt to recognise a line drawing of a carrot

38

40 41 42 43 44 45 47 51 53 59 63 64 65 69

72 72 73 75 80 81 82 83

89 90 94 101 111 114 119 121

xv

xvi

Illustrations 4.6 4.7 4.8 4.9 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10 5.11 5.12 5.13 5.14 5.15

6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 6.10 6.11 6.12 6.13 6.14 6.15 6.16

6.17

HJA’s copy of his favourite etching showing St Paul’s Cathedral, London An example of one of HJA’s drawings from memory Bruce and Young’s model of face processing Would you recognise this cow if you saw her again? The dual-store model of memory The serial position curve The effect of delayed recall on the recency effect STM forgetting when rehearsal is prevented The digit span test Alan Baddeley The computer as an analogy for WM/SM The working memory model If you must do two things at once, make sure they don’t use the same WM loop Access to the phonological loop Measuring the capacity of the visuo-spatial loop If you are going for a drive, listen to the music station not the football Revised version of the working memory model Measures of executive function can predict whether you are able to control your weight The main areas of the brain involved in working memory The encoding, storage and retrieval stages of memory The forgetting curve Picture used to make the balloons passage meaningful The levels of processing model The effect of orienting task on retrieval The revised levels of processing model Elaborative connections between memory traces The overlap between features encoded at input and features available in the retrieval cue at output Retrieval cues leading to a memory trace (Churchill) Transfer-appropriate processing The ‘wet’ and ‘dry’ contexts The recall of words by divers under ‘wet’ and ‘dry’ learning and retrieval conditions Does that biscuit bring back memories? Is this dog reminiscing about events from the past? Familiar faces – but who are they? Scores for recognition (explicit) and fragment completion (implicit) after retention intervals of one hour and one week Automatic and effortful memory systems

122 122 127 131 137 139 140 141 141 142 143 143 143 145 147 148 150 152 153 158 159 163 166 167 168 169 172 173 174 175 175 176 178 180

183 185

Illustrations 6.18

6.19 6.20 6.21 6.22 6.23 6.24 6.25 6.26 6.27

7.1 7.2 7.3 7.4 7.5 7.6 7.7

7.8 7.9 7.10 7.11 7.12 7.13

8.1 8.2 8.3 8.4 8.5

The effect of testing on subsequent retrieval of Swahili–English word pairs, after retrieval intervals of 1 day and 7 days Retrieval-induced forgetting Where did you leave your car? An old school photograph Retrieval scores for personal events from different times of an individual’s life Who is your favourite footballer of all time? The World Trade Center attack An eyewitness identifies the guilty person – but could he be mistaken? Recall performance with cognitive interview and standard interview procedures ‘So what was the weather like when you saw this man robbing the bank?’ MRI scan of a normal brain compared with the brain of an Alzheimer patient Anterograde and retrograde amnesia shown in relation to the moment of onset Memory performance for different periods from the past Brain structures involved in memory storage and consolidation MRI brain scans of a patient with lesions in the right temporal lobe caused by HSE An example of a fragmented word stimulus The performance of Korsakoff amnesics and normal control subjects on tests of explicit and implicit memory Familiarity judgements and context recollection for pictures in Korsakoffs and normal control subjects Memory systems proposed by Squire (1992) A cross-section through the human brain, viewed from the front, showing areas involved in memory function Frequent blows to the head can sometimes lead to brain injury and cognitive impairment Patient receiving electroconvulsive therapy Elderly people normally show very little memory impairment Edward Lee Thorndike The Maier (1930, 1931) two-string problem An example of the water jug problem A solution to the nine-dot problem The Tower of Hanoi problem

186 187 188 193 194 195 196 198 201 202

208 211 213 216 218 220

221 222 225 228 231 232 235 242 243 244 245 247

xvii

xviii

Illustrations 8.6 The Hobbits and Orcs problem 8.7 Analogy of electricity and water flow 8.8 The Wason selection task 9.1 The frontal lobes. Lateral view of the brain illustrating the major subdivisions of the frontal lobes 9.2 Phineas Gage’s skull. The entry and exit of the tamping iron are shown here 9.3 Phineas Gage 9.4 Card sorting task 9.5 Wisconsin Card Sorting Test 9.6 Matchstick Test of Cognitive Flexibility 9.7 Brixton Spatial Anticipation Test 9.8 An example of a problem from the Tower of London task 9.9 A diagram of the Norman and Shallice model 10.1 These BSL signs, ‘name’ and ‘afternoon’ differ only in location 10.2 Spectrogram of a spoken sentence 10.3 Testing the effect of visual context on interpretation of a sentence 11.1 Diagram of the brain showing the position of Broca’s area 11.2 Diagram of the brain showing Wernicke’s area 11.3 Wernicke’s (1881) model of speech perception and production 11.4 Lichtheim’s (1885) model of speech perception and production 11.5 Kussmaul’s (1877) model of speech perception and production 11.6 Heilman’s (2006) model of speech perception and production 11.7 Heilman’s (2006) revised model with additional module for visual object processing 11.8 Diagram of the brain showing areas responding to repetition and intelligibility 11.9 Diagram of the brain showing area associate with visual processing of words 11.10 The control of saccades 11.11 A neuropsychological model of the processing of spoken and written language 11.12 The network used by Hinton and Shallice 12.1 Mean proportion of total details of autobiographical memories that were rated as peripheral for four positive and four negative emotions

248 252 263 274 275 276 281 282 283 285 288 294

307 312 325 338 339 340 340 343 344 346 355 359 360 362 363

374

Illustrations 12.2 Free recall and cued recall as a function of mood state (happy or sad) at learning and at retrieval 12.3 Image of the amygdala, a structure that forms part of the limbic system and that is activated in many emotional states 12.4 Mean anxiety and depression scores as a function of scenario type 12.5 Percentage of rounds in which patients with damage to emotion regions of the brain, patients with damage to other regions of the brain, and healthy controls decided to invest $1 having won or lost on the previous round 12.6 Subjective value associated with decision as a function of mood (happy vs. sad) and decision strategy (intuitive vs. deliberative) 12.7 Effects of six positive emotions on persuasiveness of arguments (weak vs. strong) 12.8 Effects of mood states on judgment and decision-making 12.9 The dorsolateral prefrontal cortex is located approximately in Brodmann areas 9 and 46; the ventromedial prefrontal cortex is located approximately in Brodmann area 10 12.10 Brain regions in the anterior dorsolateral prefrontal cortex that were activated more when utilitarian decisions were made than when non-utilitarian decisions were made

377

379 382

384

389 389 390

393

393

BOXES 3.1 3.2 3.3 3.4

Shared attention Local–global (seeing the wood for the trees) Some everyday slips of action Attentional blink

80 82 88 92

4.1 Discovering one is a synaesthete: A case history 4.2 HJA: Living with visual integrative agnosia 4.3 Jeff: Living with prosopagnosia

103 121 128

7.1 7.2 7.3 7.4

207 209 214 217

Case study: Alzheimer’s disease (Ronald Reagan) Case study: Korsakoff syndrome Case study: Temporal lobe surgery (HM) Case study: Herpes simplex encephalitis (Clive W)

8.1 Expertise 8.2 Rules of inference

255 262

xix

xx

Illustrations 9.1 9.2 9.3

Three key aspects affected The case histories of AP, DN and FS Characteristics of the dysexecutive syndrome

278 291 293

Authors David Groome was Senior Academic in the Psychology Department at the University of Westminster until 2011, when he retired. However, he retains a research connection with the University, and he continues to write cognitive psychology books. Despite all this he has always considered himself to be mainly a guitarist who does psychology in his spare time. Michael Eysenck is Professorial Fellow at Roehampton University and Emeritus Professor at Royal Holloway University of London. He has produced 46 books and about 160 book chapters and journal articles leading some to accuse him of following the adage, “Never mind the quality, feel the width!” Nicola Brace is a Senior Lecturer in Psychology at The Open University. She has taught and researched cognitive psychology for over 25 years, and has come to the conclusion that when it comes to solving Sudoku puzzles understanding the brain is not nearly as useful as a good cup of tea. Graham Edgar is currently employed as a Reader in Psychology at the University of Gloucestershire. He has spent most of his career coming to appreciate that, although psychology can be applied to pretty much everything, the difficult bit is working out how. He is presently researching situation awareness in the military, health, fire-fighting and driving domains and trying to see if neuroscience can explain it. He is an optimist. Helen Edgar worked as principal research scientist at BAE SYSTEMS for more years than she cares to remember. She now divides her time between writing and consultancy regarding road traffic collisions. Her spare time is spent trying to ‘herd cats’, or at least keep her Persian off the computer whist she is writing. Tom Manly is a clinical psychologist and programme leader at the Medical Research Council Cognition and Brain Sciences Unit in Cambridge. His insatiable need for attention has led him to perform in one of the UK’s least successful bands and to attempt stand-up comedy, only one of which has been routinely associated with audience laughter. Hayley Ness is a Lecturer in Psychology at The Open University, where she chaired the largest cognitive psychology course in Europe.

xxii

Authors She is particularly passionate about memory and face processing but has a terrible memory and can’t remember people’s names. Therefore confirming the adage that people study the thing they are least proficient at. Graham Pike is Professor of Forensic Cognition at The Open University and researches eyewitness memory. He has many pet peeves, though the greatest is his hatred of name dropping… which is a real pity because he has worked with both William Shatner and Philip Glenister. Sophie Scott is Professor of Cognitive Neuroscience at the Institute of Cognitive Neuroscience, which is part of University College London. Sophie carries out research on the neural basis of vocal communication. She is also interested in laughter, both in the research lab and in her own time. Long ago in another life she was one of David Groome’s students. Elizabeth Styles is lecturer in psychology at St. Edmund Hall, University of Oxford. She has taught and examined cognitive psychology for many years and has previously written text books on the psychology of attention for Psychology Press. She has written a highly regarded book on attention, which was good practice for her contribution to the present book. When not working she likes to travel and study archaeology.

Preface We wrote this book because we felt that it filled an important gap. As far as we know it is the first textbook to cover all of the main aspects of cognitive psychology and all of their associated disorders too. We believe that an understanding of the disorders of cognition is an essential requirement for understanding the processes of normal cognition, and in fact the two approaches are so obviously complimentary that we are quite surprised that nobody had put them together in one book before. There are books about normal cognition, and there are books about cognitive disorders (usually referred to as “cognitive neuropsychology”), but there do not seem to be any other books which cover both topics in full. We feel that this combined approach offers a number of advantages. In the first place, combining normal and abnormal cognition in one book makes it possible to take an integrated approach to these two related fields. References can be made directly between the normal and abnormal chapters, and theories which are introduced in the normal chapters can be reconsidered later from a clinical perspective. We chose to keep the normal and abnormal aspects in separate chapters, as this seems clearer and also makes it more straightforward for those teaching separate normal and abnormal cognitive psychology courses. There is also one further advantage of a combined textbook, which is that students can use the same textbook for two different courses of study, thus saving the cost of buying an extra book. Another reason for writing this book was that we found the other available cognitive psychology texts were rather difficult to read. Our students found these books were heavy going, and so did we. So we set about writing a more interesting and accessible book, by deliberately making more connections with real life and everyday experience. We also cut out some of the unnecessary anatomical detail that we found in rival texts. For example, most neuropsychology books include a large amount of detail about the structure of the brain, but most psychology students do not really need this. So we decided to concentrate instead on the psychological aspects of cognitive disorders rather than the anatomical details. And finally, we decided to put in lots of illustrations, because we think it makes the book clearer and more fun to read. And also we just happen to like books which have lots of pictures. So here then is our textbook of cognitive psychology and cognitive disorders, made as simple as possible, and with lots of pictures. We enjoyed writing it, and we hope you will enjoy reading it. David Groome

Acknowledgements We would like to offer our sincere thanks to the reviewers who provided valuable comments and suggestions about our manuscript, especially Julie Blackwell Young, Rosalind Horowitz, Sam Hutton, Wido La Heij, Karla Lassonde, Wolfgang Minker, Erik Nilsen, Jane Oakhill, Fenna Poletiek, and Gezinus Wolters. Also our heartfelt thanks to Richard Kemp and Hazel Dewart, who both made valuable contributions to chapters 4 and 10 respectively. Thanks also to those at Psychology Press, and in particular Rebekah Edmondson, Michael Fenton, Ceri Griffiths, and Natalie Larkin. And finally thanks to Richard Cook and Jef Boys at Book Now.

This page intentionally left blank

Chapter 1

Contents 1.1 Cognitive processes

3

1.2 Experimental cognitive psychology

6

1.3 Computer models of information processing

10

1.4 Cognitive neuroscience and neuropsychology

12

1.5 Automatic processing

17

1.6 Minds, brains and computers

22

Summary

22

Further reading

23

Introduction to cognitive psychology

1

David Groome

1.1 COGNITIVE PROCESSES A DEFINITION OF COGNITIVE PSYCHOLOGY Cognitive psychology has been defined as the psychology of mental processes. More specifically it has also been described as the study of understanding and knowing. However, these are rather vague terms, and whilst they do provide an indication of what cognition involves, they leave us asking exactly what is meant by ‘knowing’, ‘understanding’ and ‘mental processes’. A more precise definition of cognitive psychology is that it is the study of the way in which the brain processes information. It concerns the way we take in information from the outside world, how we make sense of that information and what use we make of it. Cognition is thus a rather broad umbrella term, which includes many component processes, and this possibly explains why psychologists have found it so difficult to come up with a simple and unified definition of cognitive psychology. Clearly cognition involves various different kinds of information processing which occur at different stages.

STAGES OF COGNITIVE PROCESSING The main stages of cognitive processing are shown in Figure 1.1, arranged in the sequential order in which they would typically be applied to a new piece of incoming sensory input.

INPUT

Figure 1.1

Perception

Learning and memory storage

Retrieval

The main stages of cognitive processing.

Thinking

Key Term Cognitive psychology The study of the way in which the brain processes information. It includes the mental processes involved in perception, learning and memory storage, thinking and language.

4

Chapter 1 | Introduction

Experimental psychology

Computer modelling

Information taken in by the sense organs goes through an initial stage of perception, which involves the analysis of its content. Even at this early stage of processing the brain is already extracting meaning from the input, in an effort to make sense of the information it contains. The process of perception will often lead to the making of some kind of record of the input received, and this involves learning and memory storage. Once a memory has been created for some item of information, it can be retained for later use, to assist the individual in some other setting. This will normally require the retrieval of the information. Retrieval is sometimes carried out for its own sake, merely to access some information stored in the past. On the other hand, we sometimes retrieve information to provide the basis for further mental activities such as thinking. Thought processes often make use of memory retrieval, as for example when we use previous experience to help us deal with some new problem or situation. Sometimes this involves the rearrangement and manipulation of stored information to make it fit in with a new problem or task. Thinking is thus rather more than just the retrieval of old memories. The cognitive processes shown in Figure 1.1 are in reality a good deal more complex and interactive than this simple diagram implies. The diagram suggests that the various stages of cognitive processing are clearly distinct from one another, each one in its own box. This is a drastic oversimplification, and it would be more accurate to show the different stages as merging and overlapping with one another. For example, there is no exact point at which perception ceases and memory storage begins, because the process of perception brings about learning and memory storage and thus in a sense these processes are continuous. In fact all of the stages of cognition shown in the diagram overlap and interact with one another, but a diagram showing all of these complex interactions would be far too confusing, and in any case a lot of the interactions would be speculative. Figure 1.1 should therefore be regarded as a greatly simplified representation of the general sequential order of the cognitive processes which typically occur, but it would be more realistic to think of cognition as a continuous flow of information from the input stage through to the output stage, undergoing different forms of processing along the way. Cognitive psychology

Cognitive neuropsychology

Cognitive neuroscience

Figure 1.2

The four main approaches to studying cognitive psychology.

APPROACHES TO THE STUDY OF COGNITION There have been four main approaches to the study of cognitive psychology (see Figure 1.2).

1.1 Cognitive processes In the first place there is the approach known as experimental cognitive psychology, which involves the use of psychological experiments on human subjects to investigate the ways in which they perceive, learn, remember or think. A second approach to cognitive psychology is the use of computer modelling of cognitive processes. Typically this approach involves the simulation of certain aspects of human cognitive function by writing computer programs, in order to test out the feasibility of a model of possible brain function. The third approach is known as cognitive neuropsychology, which involves the study of individuals who have suffered some form of brain injury. We can discover a great deal about the working of the normal brain by studying the types of cognitive impairment which result from lesions (i.e. damage) in certain regions of the brain. Brain damage can impair information processing by disrupting one or more stages of cognition, or in some cases by breaking the links between different stages. The fourth approach to cognition is known as cognitive neuroscience, and this involves the use of techniques such as brain imaging (i.e. brain scans) to investigate the brain activities that underlie cognitive processing. The two most widely used brain-imaging techniques are PET scans (Positron Emission Tomography) and MRI scans (Magnetic Resonance Imaging, Figure 1.3). PET scans involve the detection of positrons emitted by radioactive chemicals injected into the bloodstream, whereas MRI scans detect responses to a powerful magnetic field. Both techniques can provide accurate images of brain structures, but MRI is better at detecting changes over a period of time, as for example in measuring the effect of applying a stimulus of some kind.

Key Term Experimental psychology The scientific testing of psychological processes in human and animal subjects. Computer modelling The simulation of human cognitive processes by computer. Often used as a method of testing the feasibility of an informationprocessing mechanism. Cognitive neuropsychology The study of the brain activities underlying cognitive processes, often by investigating cognitive impairment in brain-damaged patients. Cognitive neuroscience The investigation of human cognition by relating it to brain structure and function, normally obtained from brainimaging techniques.

Figure 1.3

An MRI scanner.

Source: Science Photo Library.

5

6

Chapter 1 | Introduction These four approaches to cognition have all proved to be valuable, especially when it has been possible to combine different approaches to the same cognitive process. The rest of this chapter deals with these approaches to cognitive psychology, starting with experimental cognitive psychology (Section 1.2), then computer modelling (Section 1.3), and finally cognitive neuroscience and neuropsychology (Section 1.4). Subsequent chapters of the book will continue to apply the same basic approaches in a more detailed study of each of the main areas of cognition.

1.2 EXPERIMENTAL COGNITIVE PSYCHOLOGY THE FIRST COGNITIVE PSYCHOLOGISTS The scientific study of psychology began towards the end of the nineteenth century. Wilhelm Wundt set up the first psychology laboratory at Leipzig in 1879, where he carried out research on perception, including some of the earliest studies of visual illusions. In 1885 Hermann Ebbinghaus published the first experimental research on memory, and many subsequent researchers were to adopt his methods over the years that followed. Perhaps the most lasting work of this early period was a remarkable book written by William James (Figure 1.4) in 1890, entitled Principles of Psychology. In that book James proposed a number of theories which are still broadly accepted today, including (to give just one example) a theory distinguishing between short-term and long-term memory.

THE RISE AND FALL OF BEHAVIOURISM

Figure 1.4

William James.

Source: Science Photo Library.

Cognitive psychology made slow progress in the early years due to the growing influence of behaviourism, an approach which constrained psychologists to the investigation of externally observable behaviour. The behaviourist position was clearly stated by Watson (1913), who maintained that psychologists should consider only events that were observable, such as the stimulus presented and any consequent behavioural response to that stimulus. Watson argued that psychologists should not concern themselves with processes such as thought and other inner mental processes which could not be observed in a scientific manner. The behaviourists were essentially trying to establish psychology as a true science, comparable in status with other sciences such as physics or chemistry. This was a worthy aim, but like many

1.2 Experimental cognitive psychology worthy aims it was taken too far. The refusal to consider inner mental processes had the effect of restricting experimental psychology to the recording of observable responses, which were often of a rather trivial nature. Indeed, some behaviourists were so keen to eliminate inner mental processes from their studies that they preferred to work on rats rather than on human subjects. A human being brings a whole lifetime of personal experience to the laboratory, which cannot be observed or controlled by the experimenter. A rat presents rather fewer of these unknown Figure 1.5 A rat learning to run through a maze. and uncontrolled variables (Figure 1.5). Source: Shutterstock. A good example of the behaviourist approach is the classic work carried out on learning by B.F. Skinner (1938), who trained rats to press a lever in order to obtain a food pellet as a reward (or ‘reinforcement’). The work of Skinner and other behaviourists undoubtedly generated some important findings, but Key Term they completely disregarded the cognitive processes underlying the Behaviourism responses they were studying.

GESTALT AND SCHEMA THEORIES Despite these restrictions on mainstream psychological research, some psychologists began to realise that a proper understanding of human cognition could only be achieved by investigating the mental processes which the behaviourists were so determined to eliminate from their studies. Among the first of these pioneers were the Gestalt psychologists in Germany, and the British psychologist Frederick Bartlett. Their work returned to the study of cognitive processes and it helped to lay the foundations of modern cognitive psychology. It is very easy to demonstrate the importance of inner mental processes in human cognition. For example, a glance at Figure 1.6 will evoke the same clear response in almost any observer. It is a human face. However, a more objective analysis of the components of the figure reveals that it actually consists of a semi-circle and two straight lines. There is really no ‘face’ as such in the figure itself. If you see a face in this simple figure, then it is you, the observer, who has added the face from your own store of knowledge. The idea that we contribute something to our perceptual input from our own knowledge and experience was actually proposed by a number of early theorists, notably the Gestalt group (Gestalt is German for ‘shape’ or ‘form’). They suggested that we add something to what we perceive, so that the perception of a whole object will be something more than just the sum of its component parts (Wertheimer, 1912; Kohler, 1925). They argued that the perception of a figure depended on its ‘pragnanz’ (i.e. its meaningful content), which favoured the selection of the simplest and best interpretation available (Koffka,

An approach to psychology which constrains psychologists to the investigation of externally observable behaviour, and rejects any consideration of inner mental processes. Gestalt psychology An approach to psychology which emphasised the way in which the components of perceptual input became grouped and integrated into patterns and whole figures.

7

8

Chapter 1 | Introduction

1935). These theories were perhaps rather vague, but they did at least make an attempt to explain the perception of complex figures such as faces. The behaviourist approach, which refused to consider any influence other than the stimulus itself, could not offer any explanation at all for such phenomena. The schema theory proposed by Bartlett (1932) was another early attempt to provide a plausible explanation for a person’s ability to make sense of their perceptual input. The schema theory proposes that all new perceptual input is analysed by comparing it with items which are already in our memory store, such as shapes and sounds which are familiar from past experience. These items are referred to Figure 1.6 A shape recognised by most observers. as ‘schemas’, and they include a huge variety of sensory patterns and concepts. Figure 1.7 illustrates the process of selection of an appropriate schema to match the incoming stimulus. (NB: This is purely diagrammatic. In reality there are probably millions of schemas available, but there was not enough space for me to draw the rest of them.) The schema theory has some interesting implications, because it suggests that our perception and memory of an input may sometimes be changed and distorted to fit our existing schemas. Since our schemas are partly acquired from our personal experience, it Figure 1.7 Schemas generated for comparison follows that our perception and memory of any with new input. given stimulus will be unique to each individual Source: Drawing by David Groome. person. Different people will therefore perceive the same input in different ways, depending on their own unique store of experience. Both of these phenomena were demonstrated by Bartlett’s experiments (see Chapter 6 for Key Term more details), so the schema theory can be seen to have considerable explanatory value. The schema approach has much in common with Schema the old saying that ‘beauty lies in the eye of the beholder’. Perhaps we A mental pattern, could adapt that saying to fit the more general requirements of schema usually derived from theory by suggesting that ‘perception lies in the brain of the perceiver’. past experience, which As a summary of schema theory this is possibly an improvement, but I is used to assist with would concede that it possibly lacks the poetry of the original saying. the interpretation of Schema and Gestalt theory had a major influence on the development subsequent cognitions, of cognitive psychology, by emphasising the role played by inner for example by mental processes and stored knowledge, rather than considering identifying familiar only stimulus and response. However, it would take many years for shapes and sounds in a this viewpoint to take over from behaviourism as the mainstream new perceptual input. approach to cognition.

1.2 Experimental cognitive psychology

TOP-DOWN AND BOTTOM-UP PROCESSING Inspired by the schema theory, Neisser (1967) identified two main types of input processing, known as top-down and bottom-up processing. Top-down processing involves the generation of schemas by the higher cortical structures, and these schemas are sent down the nervous system for comparison with the incoming stimulus. Topdown processing is also sometimes referred to as schema-driven or conceptually driven processing. Bottom-up processing is initiated by stimulation at the ‘bottom end’ of the nervous system (i.e. the sense organs), which then progresses up towards the higher cortical areas. Bottom-up processing is also known as stimulus-driven or data-driven processing, because it is the incoming stimulus which sets off some appropriate form of processing. One obvious difference between ‘top-down’ and ‘bottom-up’ processing is that their information flows in opposite directions, as shown in Figure 1.8. Bottom-up processing theories can help to explain the fact that processing is often determined by the nature of the stimulus (Gibson, 1979). However, bottom-up theories have difficulty explaining the perception of complex stimuli, which can be more easily explained by top-down theories. Although there have been disputes in the past about the relative importance of ‘top-down’ and ‘bottom-up’ processing, Neisser (1967) argues that both types of processing probably play a part in the analysis of perceptual input and that in most cases information processing will involve a combination of the two. We can thus think of input processing in terms of stimulus information coming up the system, where it meets and interacts with schemas travelling down in the opposite direction.

Key Term Top-down (or schema-driven) processing Processing which makes use of stored knowledge and schemas to interpret an incoming stimulus (contrasts with bottom-up processing). Bottom-up (or stimulus-driven) processing Processing which is directed by information contained within the stimulus (contrasts with topdown processing).

Schemas

Top-down processing

Bottom-up processing

Stimulus

Figure 1.8 Top-down and bottom-up processing.

9

10

Chapter 1 | Introduction

1.3 COMPUTER MODELS OF INFORMATION PROCESSING COMPUTER ANALOGIES AND COMPUTER MODELLING OF BRAIN FUNCTIONS A major shift towards the cognitive approach began in the 1950s, when the introduction of the electronic computer provided a new source of inspiration for cognitive psychologists. Computer systems offered some completely new ideas about information processing, providing a helpful analogy with possible brain mechanisms. Furthermore, computers could be used as a ‘test-bed’ for modelling possible human brain functions, providing a means of testing the feasibility of a particular processing mechanism. By separating out the various component stages of a cognitive process, it is possible to devise a sequential flow chart which can be written as a computer program and actually put to the test, to see whether it can process information as the brain would. Of course such experiments cannot prove that the programs and mechanisms operating within the computer are the same as the mechanisms which occur in the brain, but they can at least establish whether a processing system is feasible. Among the first to apply computers in this way were Newell et al. (1958), who developed computer programs which were able to solve simple problems, suggesting a possible comparison with human problem-solving and thought. More recently programs have been developed which can tackle far more complex problems, such as playing a game of chess. Computer programs were also developed which could carry out perceptual processes, such as the recognition of complex stimuli. These programs usually make use of feature detector systems, which are explained in the next section. Key Term Feature detectors Mechanisms in an informationprocessing device (such as a brain or a computer) which respond to specific features in a pattern of stimulation, such as lines or corners.

FEATURE DETECTORS Selfridge and Neisser (1960) devised a computer system which could identify shapes and patterns by means of feature detectors, tuned to distinguish certain specific components of the stimulus such as vertical or horizontal lines. This was achieved by wiring light sensors together in such a way that all those lying in a straight line at a particular angle converged on the same feature detector, as illustrated in Figure 1.9. This system of convergent wiring will ensure that the feature detector will be automatically activated whenever a line at that particular angle is encountered. Simple feature detectors of this kind could be further combined higher up the system to activate complex feature detectors, capable of detecting more complicated shapes and patterns made up out of these simple components, as shown in Figure 1.10. A hierarchy of feature detectors, continuing through many levels of increasing complexity, are able to identify very complex shapes such as faces. Selfridge and Neisser (1960) demonstrated that such a system

1.3 Computer models of information processing

11

I

Figure 1.9 Wiring to a simple feature detector.

Figure 1.10 Wiring to a complex feature detector.

of simple and complex feature detectors could be made to work very effectively on a computer, which suggests that it does provide a feasible mechanism for the identification of shapes and patterns. This raised the possibility that human perception could involve similar featuredetecting systems, and indeed such feature detectors have been found in the brain. Hubel and Weisel (1959) found simple feature detector cells when carrying out microelectrode recordings in the brain of a cat, and more recently Haynes and Rees (2005) have used functional imaging techniques to identify similar feature detector cells in the human brain. The discovery of feature detectors can be regarded as an example of different approaches to cognition being combined, with contributions from both neuroscience and computer modelling. The concept has also had a major influence on cognitive psychology, as feature detectors are thought to operate as ‘mini-schemas’ which detect specific shapes and patterns. This approach paved the way towards more advanced theories of perception and pattern recognition based on computer models, such as those of Marr (1982) and McClelland and Rumelhart (1986). A more detailed account of feature extraction theories can be found in Chapter 2.

12

Chapter 1 | Introduction

Signal 1 Decision channel Signal 2

Figure 1.11 Broadbent’s model of selective attention.

Signal 3

SELECTIVE FILTER (limited capacity)

THE LIMITED-CAPACITY PROCESSOR MODEL Broadbent (1958) carried out experiments on divided attention, which showed that people have difficulty in attending to two separate inputs at the same time. Broadbent explained his findings in terms of a sequence of processing stages which could be represented as a series of stages in a flow chart. Certain crucial stages were identified which acted as a ‘bottleneck’ to information flow, because of their limited processing capacity (see Figure 1.11). This was an approach to information processing which owed its inspiration to telecommunications and computing technology. There is a clear parallel between the human brain faced with a large array of incoming information, and a telephone exchange faced with a large number of incoming calls, or alternatively a computer whose input has exceeded its processing capacity. In each case many inputs are competing with one another for limited processing resources, and the inputs must be prioritised and selectively processed if an information overload is to be avoided. Broadbent referred to this process as ‘selective attention’, and his theoretical model of the ‘limited-capacity processor’ provided cognitive psychology with an important new concept. This work on selective attention will be considered in more detail in Chapter 3. But for the moment these approaches are of interest chiefly for their role in the early development of cognitive psychology.

1.4 COGNITIVE NEUROSCIENCE AND NEUROPSYCHOLOGY THE STRUCTURE AND FUNCTION OF THE BRAIN Cognitive neuroscience is concerned with the relationship between brain function and cognition, and normally makes use of brainimaging techniques. Cognitive neuropsychology is also concerned with the brain mechanisms underlying cognition, by studying individuals who have suffered brain damage. Both of these related approaches are now accepted as important components of cognitive psychology. This is not a textbook of neurology, so it would not be appropriate here to deal with brain anatomy and function in detail. However, there will be references throughout this book to various regions of the brain, so it would be useful to consider a basic working map of the

1.4 Cognitive neuroscience and neuropsychology

Motor cortex

13

Pariental lobe

Frontal lobe Occipital lobe

Wernicke’s area

Broca’s area

Temporal lobe

Cerebellum

brain. Figure 1.12 shows a side view of the human brain, showing the position of its main structures. The outer shell of the brain is known as the cerebral cortex, and it is responsible for most of the higher cognitive processes. The various lobes of the cortex are extensively interconnected, so that a single cognitive process may involve many different cortical areas. However, the brain is to some extent ‘modular’ in that certain brain areas do perform specific functions. We know this largely from the study of brain lesions, since damage to a certain part of the brain can often cause quite specific impairments. In recent years the introduction of brain scanning equipment has provided an additional source of knowledge to supplement the findings of brain lesion studies. It has been established that the left and right hemispheres of the brain have particular specialisations. In right-handed people the left hemisphere is normally dominant (the nerves from the brain cross over to control the opposite side of the body), and the left hemisphere also tends to be particularly involved with language and speech. The right hemisphere seems to be more concerned with the processing of non-verbal input, such as the perception of patterns or faces. These functions may be reversed in left-handed people, though most have left hemisphere specialisation for language. It would appear then (to borrow a football cliché) that it is a brain of two halves. But in addition to these specialisations of the right and left hemispheres, it has been argued that the front and the rear halves of the brain also have broadly different functions. Luria (1973) points out that the front half of the brain (in fact the area corresponding to the frontal lobes) is primarily concerned with output, such as for example the control of movements and speech. In contrast the rear half of the brain (the parietal, temporal and occipital lobes) tend to be more concerned with the processing of input, as for example in the analysis of visual and auditory perception.

Figure 1.12 A side view of the human brain, showing the main lobes. Source: Drawing by David Groome.

14

Chapter 1 | Introduction

Key Term Broca’s area A region of the brain normally located in the left frontal region, which controls motor speech production. Wernicke’s area A region of the brain normally located in the left temporal region, which is concerned with the perception and comprehension of speech.

The frontal lobes include the motor region of the cortex, which controls movement. Damage to this area is likely to cause problems with the control of movement, or even paralysis. Also in the frontal lobes is Broca’s area, which controls the production of speech, and it is normally in the left hemisphere of the brain. It was Broca (1861a), who first noted that damage to this region caused an impairment of speech production. Other parts of the frontal lobes are involved in the central executive system which controls conscious mental processes such as the making of conscious decisions. Recent neuro-imaging studies have shown that activation of the prefrontal cortex (the front-most region of the frontal lobes) is associated with intelligent reasoning (Jung and Haier, 2007), and prefrontal activation is also linked with the selective retrieval of memory items (Kuhl et al., 2008). The occipital lobes at the back of the brain are mainly concerned with the processing of visual input, and damage to the occipital lobes may impair visual perception (Weiskrantz et al., 1974; Gazzaniga et al., 2009). The parietal lobes are also largely concerned with perception. They contain the somatic sensory cortex, which receives tactile input from the skin as well as feedback from the muscles and internal organs. This region is also important in the perception of pain, and other parts of the parietal lobes may be involved in some aspects of short-term memory. Recent studies using brain scans suggest that the parietal lobes are activated during the retrieval of contextual associations of retrieved memories (Simons et al., 2008). The temporal lobes are so called because they lie beneath the temples, and they are known to be particularly concerned with memory. Temporal lobe lesions are often associated with severe amnesia. For example, Milner (1966) reported that a patient called HM, whose temporal lobes had been extensively damaged by surgery, was unable to register any new memories. Aggleton (2008) concludes that there is now extensive evidence linking the temporal lobes to the encoding and retrieval of memories of past events. The temporal lobes also include the main auditory area of the cortex, and a language centre known as Wernicke’s area (again usually in the left hemisphere), which is particularly concerned with memory for language and the understanding of speech (Wernicke, 1874). Over the years lesion studies have not only established which areas of the brain carry out particular cognitive functions, but they have also shed some light on the nature of those functions. For example, as explained above, Milner (1966) reported that the temporal lobe amnesic patient HM was unable to remember any information for longer than a few seconds. However, his ability to retain information for a few seconds was found to be completely normal. From these observations it was deduced that HM’s lesion had caused a severe impairment in his ability to store items in his long-term memory (LTM), but had caused no apparent impairment of his short-term memory (STM). This finding suggests a degree of independence (i.e. a ‘dissociation’) between STM and LTM. An interesting observation was

1.4 Cognitive neuroscience and neuropsychology made in a later study by Warrington and Shallice (1969), whose patient KF suffered an impairment of STM but with an intact LTM. This is an exact reversal of the pattern of impairment found in HM. It has thus been shown that either STM or LTM can be separately impaired while the other remains intact. This is known as a double dissociation, and it provides particularly convincing evidence for the view that STM and LTM involve separate processing and storage mechanisms. Later in this book there will be many references to dissociations of various kinds, but where a double dissociation can be demonstrated this is regarded as a particularly convincing argument for the independence of two functions. The study of brain and cognition obviously overlap, and in recent years cognitive psychologists and neuropsychologists have been able to learn a lot from one another. A deliberate attempt has been made in this book to bring normal cognitive psychology and cognitive neuropsychology together, to take full advantage of this relationship.

INFORMATION STORAGE IN THE BRAIN In order to operate as an information-processing system, the brain must obviously have some way of representing information, for both processing and storage purposes. Information must be encoded in some representational or symbolic form, which may bear no direct resemblance to the material being encoded. Consider, for example, how music may be encoded and stored as digital information on a silicon chip, as laser-readable pits on a CD, as electromagnetic fields on a tape, as grooves on a vinyl disc (remember them?), or even as notes written on a piece of paper. It does not matter what form of storage is used, so long as you have the equipment to encode and decode the information. There have been many theories about the way information might be represented and stored in the brain, including early suggestions that information could be stored in magnetic form (Lashley, 1950) or in chemical form (Hyden, 1967). However, neither of these theories was very plausible because such mechanisms would be unable to offer the necessary storage capacity, accessibility, or durability over time. The most plausible explanation currently available for the neural basis of information storage is the proposal by Donald Hebb (1949) that memories are stored by creating new connections between neurons (see Figure 1.13). The entire nervous system, including the brain, is composed of millions of neurons, which can activate one another by transmitting chemical substances called neurotransmitters across the gap separating them, which is known as the synapse. All forms of neural activity, including perception, speech, or even thought, work by transmitting a signal along a series of neurons in this way. These cognitive processes are therefore dependent on the ability of one neuron to activate another. Hebb’s theory postulated that if two adjacent neurons (i.e. nerve cells) are fired off simultaneously, then the connection between them will be strengthened. Thus a synapse which has been frequently

15

Key Term Double dissociation A method of distinguishing between two functions whereby each can be separately affected or impaired by some external factor without the other function being affected, thus providing particularly convincing evidence for the independence of the two functions.

Key Term Neurotransmitter A chemical substance which is secreted across the synapse between two neurons, enabling one neuron to stimulate another. Synapse The gap between the axon of one neuron and the dendrite of another neuron.

16

Chapter 1 | Introduction

Neuron (B)

Figure 1.13 Neurons and their connecting synapses. Will neuron A succeed in firing neuron B, or neuron C? Whichever neuron is fired, this will strengthen the synaptic connection between the two neurons involved. Source: Drawing by David Groome.

Neuron (A)

Axon

Dendrites

Synapse Neuron (C)

crossed in the past will be more easily crossed by future signals. It is as though a path is being worn through the nervous system, much as Cell assembly you would wear a path through a field of corn by repeatedly walking A group of cells which through it. In both cases, a path is left behind which can be more easily have become linked to followed in future. one another to form Hebb suggested that this mechanism of synaptic strengthening would a single functional make it possible to build up a network of interconnected neurons, network. Proposed which could represent a particular pattern of input. Hebb called this by Hebb as a possible a cell assembly. Figure 1.14 shows a diagrammatic representation biological mechanism of such a cell assembly, though in practice there would probably be underlying the thousands of neurons involved in each cell assembly rather than half representation and a dozen as shown here. storage of a memory Hebb argued that a cell assembly such as this could come to represent trace. a particular stimulus, such as an object or a face. If the stimulus had caused this particular group of neurons to fire simultaneously, then the neurons would become connected to one another more and more strongly with repeated exposure to the stimulus. Eventually the cell assembly would become a permanent structure, in fact a memory which could be activated by any similar stimulation in the future. Hebb’s theory has considerable explanatory value. In the first place it can explain how thoughts and memories may come to be associated with one another in memory. If two cell assemblies are activated simultaneously then some of the neurons in one assembly are likely to become connected to neurons in the other assembly, so that in future the activation of either cell assembly will activate the other. Hebb’s theory can also explain the difference between short-term and long-term memory. Hebb speculated that the temporary activation of a cell assembly by active neural firing could be the mechanism underlying short-term memory, which is known to be fragile and short-lived. However, after repeated firing the synaptic connections between the neurons in a cell assembly undergo permanent changes, which are the basis of long-term memory storage. When Donald Hebb first proposed the cell assembly Figure 1.14 A cell assembly. theory in 1949, it was still largely speculative. However, Key Term

1.5 Automatic processing since that time a great deal of evidence has been gathered to confirm that the synapse does indeed change as a result of frequent firing of the neuron. Perhaps the most convincing evidence is the discovery that when electrical stimulation is applied to living tissue taken from the brain of a rat, the neurons do actually change in a lasting way, with their threshold of firing becoming much lower so they can be more easily activated by subsequent stimuli (Bliss and Lomo, 1973). This phenomenon is known as long-term potentiation (LTP). It has also been found that rats reared in a stimulating and enriched environment, with plenty of sensory input, develop more synaptic connections in their brains than rats reared in an impoverished environment where there is little to stimulate them (Greenough, 1987). More recent research has shown that short-term storage involves the strengthening of pre-existing synaptic connections, whereas long-term storage involves the growth of new synaptic connections between the neurons (Bailey and Kandel, 2004). Brain-imaging techniques such as PET scans have also confirmed that memory storage and retrieval do in fact coincide with the activation of large-scale neural networks spread diffusely through the brain (Habib et al., 2003). There is now plenty of evidence to confirm that memory storage depends on the growth and plasticity of neural connections (De Zeeuw, 2007), and recent reviews conclude that activity-dependent modification of synaptic strength has now been established as the probable mechanism of memory storage in the brain (Bailey and Kandel, 2004; Hart and Kraut, 2007). It has taken over half a century to collect the evidence, but it begins to look as if Donald Hebb got it right.

1.5 AUTOMATIC PROCESSING AUTOMATIC VERSUS CONTROLLED PROCESSING Some of the activities of the brain are under our conscious control, but many take place automatically and without our conscious awareness or intervention. Schneider and Shiffrin (1977) made a distinction between controlled cognitive processes, which are carried out consciously and intentionally, and automatic cognitive processes, which are not under conscious control. They suggested that because controlled processes require conscious attention they are subject to limitations in processing capacity, whereas automatic processes do not require attention and are not subject to such processing limits. Automatic processing will therefore take place far more rapidly than controlled processing, and will be relatively unaffected by distraction from a second task taking up attention. Another feature of automatic processing is that it is not a voluntary process, and it will take place regardless of the wishes and intentions of the individual. For a simple demonstration of automatic processing in a cognitive task, try looking at the words in Figure 1.15, taking care not to read them. You will have found it impossible to obey the instruction not to read the message in Figure 1.15, because reading is a largely automatic process

Key Term Long-term potentiation (LTP) A lasting change in synaptic resistance following the application of electrical stimulation to living brain tissue. Possibly one of the biological mechanisms underlying the learning process. Controlled processing Processing that is under conscious control, and which is a relatively slow, voluntary process (contrasts with automatic processing). Automatic processing Processing that does not demand attention. It is not capacity limited or resource limited, and is not available for conscious inspection (contrasts with controlled processing).

17

18

Chapter 1 | Introduction

(at least for practised readers) so if you attend to the message you cannot prevent yourself from reading it. Schneider and Shiffrin suggested that cognitive processes become automatic as a result of frequent practice, as for example the skills involved in driving a car, in playing Figure 1.15 A demonstration of automatic processing. a piano, or in reading words from a page. However, we have the ability to override these automatic sequences when we need to, for example when we come across an unusual traffic situation while driving. The automatic processing of words was first clearly demonstrated by Stroop (1935), who presented his subjects with colour words (e.g. red, blue, green) printed in different coloured inks (see Chapter 3, Figure 3.3). Subjects were instructed to name the ink colours as rapidly as possible, but they were not required to read the words. Stroop found that subjects could name the ink colour far more Figure 1.16 Driving a car involves many automatic responses rapidly if it matched the word itself for an experienced driver. (e.g. the word ‘red’ printed in red ink) Source: Shutterstock. than if it did not (e.g. the word ‘red’ printed in blue ink). Since the words had a marked interfering effect on the colour-naming task despite the fact that subjects were not required to read them, it was assumed that they must have been read automatically. More recent theories about the Stroop effect are discussed in MacLeod (1998). The distinction between controlled and automatic processing has been useful in many areas of cognitive psychology. One example is face familiarity. When you meet someone you have met before, you instantly and automatically recognise their face as familiar, but remembering where and when you have met them before requires conscious effort (Mandler, 1980). Automatic processing has also been used to explain the occurrence of everyday ‘action slips’, which are basically examples of absentmindedness. For example, the author found during a recent car journey that instead of driving to his present house as he had intended, he had in fact driven to his previous address by force of habit. This was quite disturbing for the author, but probably even more disturbing for the owner of the house. Another of the author’s action slips involved absentmindedly adding instant coffee to a mug which already contained a teabag, thus creating a rather unpalatable hybrid beverage. Action slips of this kind have been extensively documented and in most cases

DO NOT READ THIS MESSAGE

1.5 Automatic processing can be explained by the activation or perseveration of automatic processes Supervisory attention system which are not appropriate (Reason, 1979). Norman and Shallice (1986) suggest that automatic processes can provide adequate control of our neural functions in most routine situations without needing to use up our attention, but they must be overridden by the conscious supervisory attention system when more complex or novel tasks require the flexibility of conscious control Automatic processes (see Figure 1.17). Crick and Koch (1990) argue that the flexibility of the conscious control Figure 1.17 The supervisory attention system model. system stems largely from its capacity Source: Adapted from Norman and Shallice (1986). for binding together many different mental activities, such as thoughts and perceptions. Baddeley (1997) suggests that this conscious control may reside in the central executive component of the working memory (see Chapter 5), which is largely associated with frontal lobe function. Johnson-Laird (1983) compares conscious control with the operating system that controls a computer. He suggests that consciousness is essentially a system which monitors a large number of hierarchically organised parallel processors. On occasion these processors may reach a state of deadlock, either because the instructions they generate conflict with one another, or possibly because they are mutually dependent on output from one another. Such ‘pathological configurations’ need to be overridden by some form of control system, and this may be the role of consciousness. Such theories add an interesting perspective to our view of automatic processing. Automatic processes are obviously of great value to us, as they allow us to carry out routine tasks rapidly and without using up our limited attentional capacity. However, automatic processes lack flexibility, and when they fail to provide appropriate behaviour they need to be overridden by consciously controlled processing. There is some evidence that this override system may be located in the frontal lobes of the brain, since patients with frontal lesions are often found to exhibit perseveration of automatic behaviour and a lack of flexibility of response (Shallice and Burgess, 1991a; Parkin, 1997). Frontal lobe functions will be examined further in Chapters 8 and 9.

CONSCIOUS AWARENESS We all have conscious awareness, but we do not really know what it is (Figure 1.18). I am quite certain that I am conscious because I experience things consciously, and you probably feel the same. We can all understand what is meant by the term consciousness as a subjective

19

20

Chapter 1 | Introduction

Key Term Blindsight The ability of some functionally blind patients to detect visual stimuli at an unconscious level, despite having no conscious awareness of seeing them. Usually observed in patients with occipital lobe lesions.

experience, yet no-one has yet been able to provide an explanation of what conscious awareness actually is, or how it might arise from neural activity. Indeed the very assumption that conscious awareness must somehow arise from the mere firing of neural circuits seems remarkable in itself. Crick (1994) calls it ‘the astonishing hypothesis’, yet it remains the only plausible hypothesis. Consciousness remains the last unexplored frontier of psychology, and arguably one of the greatest mysteries of life itself. But although we do not understand what consciousness is, we are beginning to learn a bit about what consciousness does, and the part it plays in cognitive processes. As explained in the previous section, psychologists have recently devised methods of distinguishing between processes which are consciously controlled and those which are unconscious and automatic. For example, judging whether a person’s face is familiar seems to occur automatically and unconsciously, but if we need to remember actual occasions when we have previously met them then a conscious recollection process is required (Mandler, 1980). This distinction will be considered in more detail in Chapter 6. The study of patients with certain types of brain lesion has provided particularly valuable insights into the nature of conscious and unconscious cognitive processes. For example, amnesic patients often reveal evidence of previous learning of which they have no conscious recollection. Mandler (1989) has argued that it is usually not the memory trace which is lost, but the patient’s ability to bring it into consciousness. These studies of amnesia will also be discussed further in Chapter 7. A similar phenomenon has been observed in some patients with visual agnosia (impaired perception), who can detect visual stimuli at an unconscious level but have no conscious awareness of seeing them (Weiskrantz, 1986; Persaud et al., 2007). This phenomenon is known as blindsight, and it will be examined in more detail in Chapter 4. Autism is another disorder which has shed light on the nature of consciousness, because autistic individuals appear to lack some of the characteristics of conscious processing. Their behaviour tends to be highly inflexible and repetitious, and they usually lack the ability to form plans or generate new ideas spontaneously. Autistic individuals also tend to lack the ability to develop a normal rapport with other people, and they often tend to disregard other people as though they were merely objects. Observations of such symptoms have led BaronCohen (1992) to suggest that autistic people may lack a ‘theory of mind’, meaning that they are unable to understand the existence of mental processes in others. This may provide a clue about some of the possible benefits of having consciousness. An awareness of other peoples’ thoughts and feelings seems to be crucial if we are to understand their behaviour, and it is an essential requirement for normal social interaction. Another view of the function of consciousness has recently been proposed by Seligman et al. (2013), who point out that consciousness allows us to use information from the past and the present to make

1.5 Automatic processing plans for possible events in the future. One interesting finding from an EEG study (Libet, 1985) is that when we make a conscious decision to act in some way, the conscious awareness of the decision appears to follow the actual decision, rather than preceding it. Recent fMRI research has added support to this finding (Soon et al., 2008). In view of these findings Figure 1.18 Does your dog have conscious awareness? And is he Wegner (2003) has suggested wondering the same about you? that decisions may actually be Source: Drawing by David Groome. made at an unconscious level, and conscious awareness of the decision only follows later when we observe its outcome. This is an interesting view, as it reverses the usual assumption that decisions arise from a conscious process. Indeed it is a view that questions the very existence of free will, suggesting that the impression we have of making conscious decisions may be illusory. Recently neuro-imaging studies have been used to compare the patterns of brain activation during conscious and unconscious types of perception, showing that conscious perception appears to make more use of the superior parietal cortex and the dorso-lateral prefrontal cortex (Rees, 2007). However, there is some evidence to suggest that conscious awareness may not be located in one specific area of the brain. Dehaene and Naccache (2001) argue that full conscious awareness is only achieved when several different brain areas are activated simultaneously, and possibly results from the integration of these separate inputs. It has also been pointed out that the brain areas activated during conscious activity do not necessarily indicate the location of conscious awareness in the brain, as they may just reflect a subsidiary process or prerequisite of conscious activity (De Graaf et al., 2012). The studies discussed above appear to shed some light on the nature of consciousness, but this too may be illusory. They may tell us a little about which processes involve consciousness, or which parts of the brain are involved, but we are no nearer to knowing what consciousness actually is, or how it arises. As philosopher David Chalmers (1995) puts it, we are addressing ‘the easy questions’ about consciousness, but making no progress at all with ‘the hard question’, which is the question of how conscious awareness actually arises from neural activity. McGinn (1999) suggests that human beings will never fully understand the nature of consciousness, because it may be beyond the capability of the human brain to do so. Blackmore (2003) takes a somewhat more optimistic view. She believes that understanding consciousness will one day be possible, but only if we can find a totally different way of thinking about consciousness, since

21

22

Chapter 1 | Introduction there is apparently something fundamentally wrong with our present approach. For the moment I tend to side with the pessimists and the killjoys, if only because the best brains in the known universe have been working on the problem of consciousness for many centuries without making much progress. I hope that someone will one day prove me wrong.

1.6 MINDS, BRAINS AND COMPUTERS INTEGRATING THE MAIN APPROACHES TO COGNITION It has been argued in this chapter that our present understanding of cognitive psychology has arisen from the interaction between experimental cognitive psychology, cognitive neuroscience, cognitive neuropsychology, and computer modelling. These same four approaches provide the subject matter of the rest of this book, and they will be applied to each of the main areas of cognitive processing in turn. These areas are perception, attention, memory, thinking, and language, and there will be a separate chapter on each of these processes. A unique feature of this book is that each chapter (or pair of chapters) on a particular cognitive process is followed by a chapter dealing with its associated disorders. This approach is intended to provide you with a thorough understanding of both normal and abnormal cognition, and also an understanding of the relationship between them.

SUMMARY t
Cognitive psychology is the study of how information is processed by the brain. It includes the study of perception, learning, memory, thinking and language. t
Historically there have been four main strands of research which have all contributed to our present understanding of cognitive psychology. They are experimental cognitive psychology, cognitive neuroscience, cognitive neuropsychology and computer modelling of cognitive processes. t
Experimental cognitive psychology has provided theories to explain how the brain interprets incoming information, such as the schema theory which postulates that past experience is used to analyse new perceptual input. t
Computer modelling has provided models of human cognition based on information-processing principles, and it has introduced important new concepts such as feature detector systems and processors of limited channel capacity. t
Cognitive neuropsychology provides knowledge about brain function, based on the study of people who have suffered cognitive impairment as a result of brain lesions.

1.6 Minds, brains and computers

t
Cognitive neuroscience makes use of brain-imaging techniques to investigate the relationship between brain function and cognition. t
The science of cognitive psychology has generated new concepts and theories, such as the distinction between top-down and bottom-up processing, and the distinction between automatic and controlled processing. t
The study of consciousness has yielded some interesting findings but at present we have no real understanding of what consciousness is, or how it arises from neural activity.

FURTHER READING t
Blackmore, S. (2003). Consciousness. London: Hodder Arnold. Susan Blackmore embarks on a search for human consciousness. She doesn’t find it, but the search is interesting. t
Esgate, A. and Groome D. et al. (2005). Introduction to Applied Cognitive Psychology. Hove: Psychology Press. This book is about the applications of cognitive psychology in real-life settings. I have nothing but praise for this text, though this is possibly because I am one of the authors. t
Eysenck, M.W. and Keane, M. (2010). Cognitive Psychology: A Student’s Handbook. Hove: Psychology Press. This book covers many of the same topics as our own book, but with a bit more detail and less emphasis on clinical disorders. In fact Eysenck and Keane has become something of a classic over the years, and it is a very thorough and well-written book.

23

Chapter 2

Contents 2.1 Introduction

25

2.2 Visual perception

25

2.3 Auditory perception

50

2.4 Haptic perception

58

2.5 Conclusion

67

Summary

68

Further reading

69

Perception Graham Edgar, Helen Edgar and Graham Pike

2

2.1 INTRODUCTION Our perception of the world is something that we often tend to take for granted. We detect the sights, sounds, smells, etc. of things around us, and (sometimes) recognise objects and make decisions about how we are going to interact with them. It all seems so simple – until you try to work out how the process of perception operates. There are many theories of perception and they can appear to be quite different and, indeed, sometimes contradictory. It is possible that some of the theories are right and any contradictory theories are wrong, but it is more likely that the various theories are just looking at different aspects of a very complicated process. As an analogy, imagine trying to produce a theory of how a car works. One theory could be based on which pedals need to be pressed to make the car go, another could present the theory of the internal combustion engine. Both theories would provide valuable insight into how the car works, but would appear to be quite different. This chapter will provide an overview of a number of theories and will attempt to reconcile the different theories to give an impression of how perception ‘works’.

2.2 VISUAL PERCEPTION THEORIES OF PERCEPTION – SCHEMAS AND TEMPLATE MATCHING The Grimm’s fairy tale of ‘Little Red Riding Hood’ (Grimm and Grimm, 1909; first published 1812), illustrated in Figure 2.1, is an excellent illustration of a problem that lies at the very heart of the process of perception. Little Red Riding Hood is fooled, and ultimately eaten (although there is a happy ending) by a wolf that tricks her, masquerading as her grandmother. So a key issue for perception (and for Little Red Riding Hood!) is how do we recognise an object such as a chair or our grandmother? Just as importantly, how do we recognise when an object has changed and granny has, for instance, been replaced by a scheming and very hungry wolf? Well, one way to recognise your grandmother would be to have an internal schema or ‘template’ that could be compared with incoming sensory information. If the incoming sensory information matches the grandmother template then

Key Term Perception The subjective experience of sensory information after having been subjected to cognitive processing.

26

Chapter 2 | Perception

Figure 2.1 ‘But, Grandmother, what big teeth you’ve got.’ Source: Drawing by David Groome.

Figure 2.2 Stimuli of the kind used by Shepard and Metzler (1971). The participants’ task was to judge whether or not the figure on the right was a rotated version of the one on the left (as in the top pair above) – or a different figure (as in the bottom pair). Source: Adapted from Shepard and Metzler (1971).

Key Term Templates Stored representations of objects enabling object recognition.

she is recognised. The template theory is essentially a development of the schema theory introduced in Chapter 1, as it is a system which uses information from past experience to make sense of a new stimulus. There is some evidence for the existence of internal templates. For instance, Shepard and Metzler (1971) did experiments that required people to say whether two shapes (such as those shown in Figure 2.2) were the same or different (e.g. mirror images). The more the picture of one shape was rotated from the other, the longer it took people to make a decision. This suggests that people could be rotating a template of one shape to see if the second shape fits it. This does suggest that people are able to form internal representations of an external

2.2 Visual perception

27

figure and manipulate them. There is, however, a difference between generating an internal representation of a specific, and very simple, external stimulus, and having a stored template that is general enough for ‘grandmother’. This issue will be considered in more detail later. However, template matching can only occur (if it occurs at all) after information from the outside world has been encoded in some way by the visual system. This, in itself, is not a trivial problem. For instance, in the Shepard and Metzler task, how do we pick the shape out from the background and work out just what we are going to compare with our template?

THE GESTALT APPROACH The issue of how objects are defined was central to the theories developed by the Gestalt approach (Rubin, 1915; Wertheimer, 1923), which was introduced in Chapter 1. A key issue addressed by the Gestalt psychologists was the way that we might segregate the world into figures and Figure 2.3 A reversible figure. If you concentrate on the black area as the figure then you will see a the background against which they appear. This vase, if you concentrate on the white areas then may sound trivial but is crucial as, if we are you will see a well-known person talking to himself. to recognise objects, we need to be able to tell Source: Adapted from Rubin (1915) by Helen Edgar. them apart from everything else. The importance of figure and ground can be illustrated by one of the well-known reversible figures shown in Figure 2.3. If you consider the white area to be the ‘figure’ and the black area the ‘ground’ then you see a vase. If you consider the black area to be the figure and the white area to be the ground then you see two faces. The picture is the same, the pattern of light falling on the Key Term retina of the eye is the same, but it can be segregated into figure and ground in different ways. Being able to see the same stimulus in more Reversible figure than one way demonstrates the influence on perception that organising A figure in which things into figure and ground can have. Before deciding which part the object perceived of the scene is the figure and which parts are ground it is necessary to depends on what decide which parts of a visual scene constitute a single object. Gestalt is designated as psychologists proposed a number of laws of perceptual organisation ‘figure’ and what that could be used to group parts of a visual scene into objects. Two of is designated as these laws are illustrated in Figure 2.4. ‘(back)ground’. While appealing, the Gestalt approach only covers a small part of Laws of perceptual the process of visual perception. For instance, using Gestalt laws we organisation could work out which parts of the visual scene are objects that we Principles (such as might be interested in, and compare them with a template to decide proximity) by which what they are. Both the Gestalt and template-matching theories are, parts of a visual scene however, rather vague in specifying how we might get information can be resolved into into the ‘system’ in the first place, although a possible mechanism is different objects. provided by feature-extraction theories.

Chapter 2 | Perception

28

A

FEATURE-EXTRACTION THEORIES

Feature detectors were introduced in Chapter 1 as a possible mechanism for extracting the features contained in an incoming stimulus. In many ways, feature-extraction theories are simply a variation on template theories; B it is just the nature of the template that is different. Rather than trying to match an entire object (such as a grandmother) to a template, feature-extraction theories look to break objects down into their component features. The process is basically still template matching, but with features of the object rather than the whole thing at once. A key issue, of course, is just what constitutes a feature? Little Red Riding Hood appears (unsuccessfully) to have been applying a form of feature extraction in order to recognise her grandmother (picking out ears, eyes, hands and, finally, teeth). Perhaps one of the nicest conceptualisations of the feature-extraction Figure 2.4 Examples of Gestalt laws of perceptual approach was Selfridge’s Pandemonium organisation. (A) Demonstrates the law of proximity. Items model (Selfridge, 1959) which is illustrated that are grouped close together tend to be considered as in Figure 2.5. The way that the model works part of the same object and so (A) is usually perceived as five slanted lines of dots rather than three horizontal lines. is that there are layers of ‘demons’. Demons (B) Demonstrates the law of similarity. Although the circles at the lowest level in the system (remember can be ‘grouped’ in many different ways it appears to be this is essentially a bottom-up approach) natural to group them on the basis of common colour. look for very simple features (such as lines or angles). Each demon looks for only one feature. If they ‘see’ it, they shout. Demons at the next level up listen and only respond if certain combinations of demons shout. If this happens, then they have detected a more complex feature (such as a line-junction), and they will shout about that. So each level of demons detects more and more complex features, until the object is recognised. Of course, as many demons are likely to be shouting at once it will be pandemonium, hence the name. Key Term Most people would probably not believe that we have little demons Features in our brain, but the feature-extracting computer model of Selfridge Elements of a scene and Neisser (1960) discussed in Chapter 1 suggests that the general that can be extracted approach is workable. Furthermore, there has long been evidence to and then used to build suggest that, at least at the lower levels of the visual system, there are up a perception of the cells that do the job of Selfridge’s demons. For instance Kuffler (1953) scene as a whole. See demonstrated that cells in the cat retina (ganglion cells) responded to also ‘geons’. a spot of light at a particular position in the visual field. Hubel and Pandemonium Wiesel (1959) found cells in the cat’s brain (in the visual cortex) that A fanciful but responded to edges and lines. These cells receive inputs arising from appealing conceptual ganglion cells and, of course, you can construct relatively complex model of a feature features such as edges and lines from simple features such as spots. extraction process. Modern brain-imaging techniques also support the existence of ‘feature detectors’ in the human brain (Haynes and Rees, 2005). Thus

2.2 Visual perception

29

E

?

B!

B Decision demon

B B R

Image demon

Pattern demons Angle demons

Line e de demons o s

there is a physiological basis for feature-extraction theories, at least at the ‘lower’ levels of the visual system. Breaking an image down into its component features is a useful way of coding information within the visual system, but the difficult part is working out how the different features can be interpreted and used to recognise an object. Essentially, they have to be put back together again.

MARR’S COMPUTATIONAL THEORY Marr (1982) developed an approach that concentrated on the implementation of some of the processes discussed above, progressing through a number of stages until an internal representation of the viewed object is achieved. The first stage is called the raw primal sketch when features such as circles and lines are extracted from the image. In particular, Marr proposed that the visual system can use natural constraints to work out which features form the borders of an object. For instance, a border that is created by the edge of an object tends to have a greater and more sharply defined change in luminance than an edge caused by, for instance, a shadow. Once the features have been identified, they can be grouped according to Gestalt principles and these groups of features then define the surface of the object. This is referred to as the 2½-D sketch. This sketch is only 2½-D and not 3-D as it is a representation of an object – but only from the viewpoint of the person looking at it. From this 2½-D sketch a 3-D sketch can be constructed (although Marr was a little vague about the details of how this might be done) to give a ‘full’ representation of the object that is independent of the viewer (that is, there may be

Figure 2.5 Pandemonium (Selfridge, 1959). The heavier arrows illustrate which demons are shouting the loudest! Source: Adapted from Lindsay and Norman (1972). Demon artwork by Helen Edgar.

Key Term Primal sketch First stage in Marr’s model of vision, which results in computation of edges and other details from retinal images. 2.5-D sketch Second stage in Marr’s model of vision. Aligns details in primal sketch into a viewer-centred representation of the object. 3-D sketch Third stage in Marr’s model of vision. This is a viewer-independent representation of the object which has achieved perceptual constancy or classification.

30

Chapter 2 | Perception a representation of parts that the viewer cannot see directly). Marr and Nishihara (1978) suggest that this 3-D representation can then be compared against previously stored representations, and the object can be recognised. This approach thus rather nicely combines feature extraction and template matching into a plausible theory.

BIEDERMAN’S RECOGNITION-BY-COMPONENTS APPROACH Key Term Geons Basically features, but conceived explicitly as being 3-D features. Parallel distributed processing (PDP) approaches Stimuli are represented in the brain, not by single neurons, but by networks of neurons. An approach sometimes used to model cognitive processes.

There have been many developments of Marr’s general approach such as the theories developed by Biederman (1987) which, again, are based on feature extraction. In this case, however, the features are three-dimensional and are referred to as geons. Biederman devised a system using 36 basic geons such as cones, cylinders and blocks that could be used to construct a vast range of objects. The basic principle of Biederman’s theory was that if we can identify the geons that make up an object, then we can recognise that object. One problem with this (and other feature-extraction theories) is that it is relatively easy to imagine that very different objects (such as a car and a tree) can be recognised and discriminated quite easily, but it is more difficult to imagine how the process might deal with more subtle distinctions (such as discriminating two different faces). As well as the problem of discriminating between different objects, there is also the problem of how to recognise changes in the same object. This issue presents a particular difficulty for template-matching approaches. In the Shepard and Metzler (1971) study discussed earlier, the template matching is fairly simple. A clearly defined stimulus (the block shape) can, conceptually, be internalised as a template and used for comparison with another shape. Both shapes are relatively simple and fixed. But consider what happens with more complex and changeable stimuli, such as your grandmother. It is plausible that you could recognise your grandmother by comparing the incoming visual input with an internal ‘grandmother template’, and perhaps there is even one special cell, a ‘grandmother cell’ (for a discussion of the origin of this term see Rose, 1996), in your brain that fires when (and only when) you see your grandmother. The problem occurs if there is some change in your grandmother (such as being replaced by a wolf for instance). Would the template still work? What happens if she is facing away from you? Would you need a ‘grandmother facing the other way’ template as well? You may end up with the impossible situation of requiring a template for every possible view and orientation of your grandmother; and all other objects as well. While there are many neurons in the brain, this is still rather impractical.

PARALLEL DISTRIBUTED PROCESSING APPROACHES One way of getting around the problem of needing an almost infinite number of ‘grandmother cells’ in the brain is provided by parallel distributed processing (PDP) models (Rumelhart and McClelland, 1986). PDP models are also sometimes referred to as connectionist or neural network models and these models, when implemented on computers,

2.2 Visual perception attempt to model the way in which the brain may work. In some ways, PDP approaches are still template approaches but the templates are much more flexible and, given that they represent stored knowledge, they are another conceptualisation of the schema described in Chapter 1. Crucially, any object can be represented not by the activation of a single neuron, but by the activation of many cells forming a network. Thus an object is represented not by the activity of a single cell, but by a pattern of activity across many cells. Initially, this may seem to make the problems discussed above worse. Now you need not just one cell to represent an object but many. The key point, however, is that any one cell can form a part of many different networks (as exemplified by the work of Hebb discussed in Chapter 1). It is the connections between cells that are important as much as the cells themselves. Neural networks also have the ability to make the object recognition process much more ‘fuzzy’. If the object doesn’t quite match the template, not all the cells in the network may be activated, but many of them may be. Thus, the system can make a ‘best guess’ at what the object is most likely to be. Given feedback on whether the guess is right or wrong (this can be done in the real world by simply gathering more information) the system can learn and the networks can change and adapt. If your grandmother is replaced by a wolf, some parts of a grandmother network may be activated (by the clothes and bonnet, etc.) but, hopefully, so will some parts of a ‘wolf network’. Given further feedback as to what the object is (getting eaten in Little Red Riding Hood’s case – feedback in the truest sense) you will learn to recognise the wolf more easily. The notion that the object recognition process can learn is an important one. Apart from anything else, without learning it would be impossible to recognise any new objects. Learning implies stored knowledge (whether as templates, within neural networks, or in some other form) and this is something that most of the theories discussed above do not address in detail. This is not a criticism of the theories but reflects the fact that the theories discussed so far mostly concentrate on bottom-up processing. They are thus attempting to explain how sensory information gets into the visual system to be processed further. All the theories do, however, have some aspect of top-down schema-driven processing incorporated into them (e.g. templates or neural networks). This reflects the fact that perception is essentially the interface between the physical world and our interpretation of it (more in the next section). Thus, at different levels of perception there is a changing balance, moving from simply encoding and transmitting information from the outside world to interpreting and making sense of it. It is often hard to appreciate the difference between these different aspects of perception, however, until something goes wrong. When something does go wrong with our perceptual system and what we perceive does not truly represent the outside world we usually refer to this as an illusion, and the study of such illusions provides valuable insights into how perception operates at different levels.

VISUAL ILLUSIONS Richard Gregory (1997) has attempted a classification of illusions. One of the dimensions of this classification is essentially the contribution

31

Key Term Knowledge Information that is not contained within the sensory stimulus. Illusions Cases in which perception of the world is distorted in some way.

32

Chapter 2 | Perception

of bottom-up and/or top-down processes to the generation of the illusion. This then gives a rather satisfying continuum running from those illusions that arise from the physical properties of the world to those that arise largely from the cognitive processes of the mind. For instance, at the ‘lowest’ level are illusions that are really nothing to do with the sensory processes at all, and these illusions would include such things as rainbows and mirages. They arise from physics, not perception. At the next level are the illusions that do arise from basic properties of the perceptual system but are really not influenced by cognitive processes. An example of an illusion of this type is provided by the Hermann grid, named after Ludimar Hermann in 1870, and shown in Figure 2.6. The illusory spots at the Figure 2.6 The Hermann grid. Illusory grey intersections are supposedly due to the lateral spots should be visible at the intersections of the connections between cells in the retina, with no white lines. Interestingly, the spot is usually not so top-down influences evident. obvious at the junction that you are fixating on. Perhaps the most interesting illusions, however, are those that are generated as a result of topdown influences on perception. These illusions provide strong evidence for the notion that what we know affects what we perceive. One of the most well-known illusions of this type is shown in Figure 2.7. This is the Müller-Lyer illusion, first reported by Franz Müller-Lyer in 1889. The illusion is that, although the two vertical lines are actually the same length, the one on the left is perceived as being longer. The theories discussed so far cannot easily explain such an effect without reference to top-down influences. For instance, a simple feature-extraction approach should not be biased by the precise arrangement of the features (the left and right figures are both made up of the same features) so that this suggests that something beyond what is present in the image is influencing our perception of it. Richard Gregory (1966) (whose theories we will discuss in more detail later) suggested that, although the figure is just a two-dimensional arrangement of lines, Figure 2.7 The Müller-Lyer illusion. The vertical we interpret them using our knowledge and line on the left appears to be longer than the one experience of a three-dimensional world. Thus, on the right, even though they are actually the Gregory suggests that we see the illusion as two same length. corners (as shown in Figure 2.8) with one corner going away from us (and so appearing more distant) and the other coming towards us (and so appearing closer). To explain the illusion, we have to accept that we also ‘know’ that things that are further away give rise to a smaller image on our retina and we

2.2 Visual perception

33

Figure 2.8 A possible explanation for the Müller-Lyer illusion. The figures are perceived in three dimensions as illustrated here and this leads to distortions of perceived size. Source: Drawing by David Groome.

scale them up to make allowances for this (we don’t perceive people as shrinking in size as they walk away from us). This is an example of size constancy. In the illusion the two lines are actually the same length, but one appears to be further away and so is scaled up by our visual system, giving the impression that it is longer. Support for the role of knowledge and experience in the interpretation of the Müller-Lyer illusion also comes from a study of the Bete people (Segall et al., 1963) who live in a dense jungle environment with relatively few corners. The Bete people do not perceive the MüllerLyer illusion as strongly as do Europeans, providing support for the role of knowledge and experience in the interpretation of the figure. It is possible to get an idea of the influence of our ‘square world’ on perception by considering another illusion, the Ames room (invented by one Adelbert Ames), which is shown in Figure 2.9. The two figures in the room appear to be of vastly different size even though they are, in fact, identical in size. The explanation becomes clear when we see the shape of the room. The room is distorted so that from one viewpoint only (shown by the arrow in the figure) it appears to be a ‘normal’ square room. In actual fact, one corner is much further away than the other. Thus, although it appears that both the little figures are the same distance away from us (so we do not do any scaling up as we do in the Müller-Lyer illusion) one is actually much further away, giving rise to a much smaller retinal image. The distorted perspective cues mean that the viewer does not ‘know’ that one figure is further away than the other, and so no rescaling to maintain size constancy occurs. It is even possible to get the Ames room illusion without the room. In fact, all you need to do is to move something, such as the lighthouse in Figure 2.10, out of its ‘normal’ depth plane within a picture to reveal how much size constancy influences the perceived size of objects. There is still some debate as to how much top-down influences are responsible for illusions. For instance, there are explanations of the Müller-Lyer illusion that do not rely on top-down processing (e.g. Day, 1989) It is, however, hard to explain all illusions without at least some reference to the influence of top-down cognitive processes

Key Term Size constancy The perceived size of objects is adjusted to allow for perceived distance.

34

Chapter 2 | Perception

Figure 2.9 The Ames room. Two identical figures (left) appear to be of very different sizes. This is due to the unusual shape of the room (right). Source: Photographs by Graham Edgar.

Figure 2.10 When size constancy breaks down. Moving objects (or people) out of their natural position in a scene reveals how much our visual system automatically compensates for changes in retinal image size with object distance.

based on knowledge and experience, and there is evidence from brainimaging studies (Hayashi et al., 2007) that both bottom-up and topdown processes are involved in the perception of perspective illusions. As discussed previously, however, knowledge in this context should be interpreted rather more broadly than, for example, ‘Something I learned in school.’ Size constancy, for example, is based on an individual ‘knowing’ that objects that are further away generate a smaller retinal image. Individuals are, however, rarely aware that such knowledge is being used to influence their perceptions, or even of acquiring such knowledge in the first place. It is only when size constancy fails that we really become aware of how much top-down processing is influencing our perception. Pure bottom-up processes rely only on information gleaned from incoming sensory information, whereas top-down processes also use information that is not present

2.2 Visual perception

35

within the sensory information, such as knowledge of the way the world usually is. So ‘knowledge’ could be broadly interpreted as any information that resides in the perceiver, rather than being contained within the stimulus that is being perceived. Thus the Gestalt laws could be considered to be a form of implicit knowledge, likewise the precise configuration of neural networks. They represent information held within the individual, and not the stimulus. If knowledge is involved in the perception of illusions then certainly a definition beyond ‘Things learned in school’ is necessary, as the perception of illusions appears to be the preserve not only of humans. There is evidence, for example, that pigeons perceive the Müller-Lyer illusion (Nakamura et al., 2006), although it is not clear whether jungle-dwelling pigeons would be less susceptible (see the Segall et al. (1963) study on the Bete people). Furthermore, there is evidence that some non-human species not only perceive illusions, they actively create them. For example, some male bowerbirds build ‘avenues’ (where the female will stand to view the male mating display) using two parallel walls of sticks that lead onto a ‘court’ consisting of grey or whitish objects (pebbles, bones, etc.) on which the male will stand to display coloured objects (Figure 2.11). Remarkably, the grey and white objects are carefully arranged so that the larger objects are placed further away from the avenue, leading to a distortion of perspective rather like that in the Ames room. Essentially, the court will appear foreshortened (to humans and, presumably, to the female bowerbird). Such an arrangement appears to be quite deliberate. If the size gradient of the objects is reversed by curious humans (Endler et al., 2010) the male bowerbird will move the objects to re-establish the original gradient. Of course, the illusion created by the male bowerbird can only work from one viewpoint (as does the Ames room). Probably not entirely by chance, the viewpoint of the female bowerbird is constrained by the avenue of twigs. Quite what effect the illusion has on the perception of the female is unclear but it seems likely that there is an effect, as there is evidence (Kelley and Endler, 2012) that the more regular the resulting pattern from the point of view of the female (and thus the better potential illusion), the greater the mating success of the male. Surely this is one of the more unusual applications of a visual illusion. Returning again to humans, the use of knowledge as a part of top-down processing allows us to interpret incoming sensory information, rather than just encoding it. It also means that our final perception of the sensory information may (as we have already seen) be strongly influenced by what we already know. The rest of this section on visual Figure 2.11 The avenue and court (strewn with brightly perception will consider in more detail coloured ornaments) carefully constructed by the male the role of knowledge in perception, bowerbird to woo the female. particularly when considering perception Source: Shutterstock.

36

Chapter 2 | Perception in the ‘real world’ (as opposed to the laboratory). Crucially, the distinction between sensation and perception will be considered and two further theories of perception will be discussed that differ markedly in the importance they place on the role of knowledge in perception.

Figure 2.12

‘Well I never expected that!’

Source: Drawing by Dianne Catherwood.

Key Term Sensation The ‘raw’ sensory input (as compared with ‘perception’).

THE DIFFERENCE BETWEEN SENSATION AND PERCEPTION

Imagine that you are in a car driving along a road that you do not know. The road disappears around a bend. What do you do? If it were not for your top-down processing, you would probably have to get out of the car and peer around the corner to check that the road does, in fact, continue and that there are no other unexpected occurrences such as that in Figure 2.12. In ‘real life’, however, you will almost certainly proceed round the bend, secure in the knowledge that roads tend to continue and do not simply terminate without warning. An example such as this, while superficially rather silly, emphasises just how much we rely on what we know to influence almost everything that we do. It is now worth defining what we mean by sensation and perception. Sensation will be considered to be the ‘raw’ bottom-up input from the senses and perception will be considered to be the end result of the processing of that sensory material within the visual system. The individual may be consciously aware of the perception arising from incoming sensory information, or they may not (subliminal perception). Sensation and perception thus lie at opposite ends of the visual process and may well be quite different. That is, what pops out of the ‘top’ of the system as perception may be a highly modified version of what went in at the ‘bottom’ of the visual system as sensation. It is beyond the scope of this chapter to discuss subliminal perception, so the following discussion will focus on perception as a conscious awareness of the output of the visual system. It is possible that not all the information that is sensed will reach perception at all. Some of the sensory information entering the visual system may be filtered out by attentional processes (discussed briefly in Chapter 1, and in detail in Chapter 3) and will not form a part of our perception. This chapter has also considered that what we already know may influence what we perceive and so perception may represent not only a filtered, but also a modified, version of the original sensation. A simple diagram of the route from sensation to perception is presented in Figure 2.13. Different parts of the process may also interact; what we know may influence the way that attentional filtering operates, as well as our final perception of the sensory information. It should thus be noted that the process described above is a very simplified version of what appears to be happening in the processing of visual input.

2.2 Visual perception

37

The philosopher Immanuel Kant Perception refers to the objects or events that Knowledge exist independently of the senses as numena and our experience of those objects and events as phenomena. Kant argued that we can never truly access the numena, only the Attention phenomena. That is, we can never know the world as it truly is, only our perception of it after it has been filtered and modified by our senses and cognitive processes. There is a saying that is often attributed to Kant Sensation which sums up perception, and which runs, ‘We see things not as they are, Figure 2.13 The components of perception. Raw sensory but as we are.’ To illustrate the difference between information is filtered and combined with knowledge to form sensation and perception and the the overall percept. Note that information is seen as flowing top-down as well as bottom-up at all stages. complex processes that operate in between, we will return to the discussion about driving and, in particular, accidents that occur while driving. Generally, those individuals who are most likely to have an Key Term accident while driving lie at the ends of the age range for drivers Numena (Claret et al., 2003). Young drivers (under 25) and older drivers (75+) The world as it tend to have an increased risk of accidents, whereas those drivers in really is. See also between have a lower risk of being involved in an accident. This is ‘phenomena’. the case for most types of accident, with one notable exception. These are accidents that are usually referred to as ‘looked but failed to see’ Phenomena (LBFS) accidents (Sabey and Staughton, 1975). Numena as we perceive them.

‘LOOKED BUT FAILED TO SEE’ (LBFS) ACCIDENTS ‘Looked but failed to see’ accidents refer to occasions when drivers have crashed into something and claimed subsequently that they simply ‘did not see it’, even though the object they have just hit should be easily visible (see Figure 2.14). This is where the distinction between sensation and perception becomes particularly important. Undoubtedly, some accidents are due to a failure of sensation. Fairly obviously, if an object is not within a driver’s field of view (for example they are not looking where they are going), they will not detect it visually and may crash into it. Sensing an object, however, involves more than just detecting the light coming from it. Even if light from

Figure 2.14 High sensory conspicuity does not guarantee accurate perception. . . Source: Photograph courtesy of Gloucestershire Constabulary.

38

Chapter 2 | Perception

the object does reach the eyes of a driver, this does not guarantee that they will become aware of it. Earlier in the chapter the Gestalt approach emphasised the importance of picking an object out from its background, and Marr provided a possible process by which this could be done. But what if it is difficult, or impossible, to discriminate an object from its background? The visual system may sense the light reflecting from that object (so you could argue that the system has ‘detected’ it) but the light from the object, Figure 2.15 The effect of contrast on detectability. The and the light from the background, may pedestrian on the left of the picture is silhouetted against be too similar to tell one from the other. the oncoming headlights which increase the contrast For example, a pedestrian at night can be between the pedestrian and the background; increasing extremely difficult for a driver to pick out detectability. The pedestrian on the right presents against a from the background (see Figure 2.15) lower contrast background, and is harder to detect. because of the lack of contrast between Source: Shutterstock. the pedestrian and the background against which they are seen. The term used to describe how easily an object can be detected by the senses is sensory conspicuity, and Key Term refers to the intrinsic properties of an object (such as shape, colour, brightness, amount of noise that it is making) that are likely to be Sensory conspicuity registered by the senses – usually as a result of increasing contrast with The extent to which the background. Thus, a pedestrian can often increase their sensory aspects of a stimulus conspicuity by carrying a torch, or wearing reflective material. (such as colour and Research by Cole and Hughes (1984) has suggested that sensory luminance) influence conspicuity, although necessary for the detection of objects, may not how easily it can always be sufficient for an individual to become aware of that object be registered by and take action to avoid it. Cole and Hughes suggest that in order the senses. See to be able to consciously perceive (and react to) an object, it should also ‘attention also have high attention conspicuity. This term refers to the fact that conspicuity’. to perceive something, the individual’s senses need to detect that it is Attention there and, in addition, the individual has to attend to the information conspicuity provided by the senses. The discussion of attention above, and that The interaction of in Chapter 3, suggests that much information that we sense is not aspects of a stimulus attended to. There is an interesting distinction that can be made here (such as colour, between sensory conspicuity and attention conspicuity. As mentioned luminance, form) above, sensory conspicuity relates mainly to aspects of the object being with aspects of an perceived (brightness, etc.), whereas attention conspicuity is more individual (such as likely to be influenced by aspects of the individual doing the observing attention, knowledge, (previous experience, expectations, etc.). Broadly speaking, sensory pre-conceptions) that conspicuity relies primarily on bottom-up processing whereas attention determine how likely conspicuity is more heavily influenced by top-down processes. At most a stimulus is to be road junctions, for example, the class of road user that a driver is most consciously perceived. likely to have to avoid is other cars – and thus a driver may be biased See also ‘sensory towards searching for cars; their search for hazards is influenced by conspicuity’. what they expect to be there (Hills, 1980; Theeuwes and Hagenzieker,

2.2 Visual perception 1993). Objects that do not conform to the size, shape and speed of a car (such as a cyclist) are therefore less likely to be attended to, and more likely to be hit (Räsänen and Summala, 1998). Thus if a driver is not expecting a motorcyclist at a particular location they may drive into them, even if the motorcyclist has high sensory conspicuity. It is this class of accident that may be referred to as LBFS. In accidents of this kind the object that is hit may be of very high sensory conspicuity, and it appears almost certain that the driver would have looked in the general direction of the object and, at a sensory level, detected it. Unfortunately, although the driver looked in the region where the hazard was, they didn’t ‘see’ it. That is, although the object was registered by the driver’s senses, they did not attend to it, become consciously aware of it, or take action to avoid it. Is there any evidence that accidents of this kind occur? Martin Langham and his co-workers (Langham et al., 2002) looked at accidents involving vehicles that have perhaps the highest sensory conspicuity of any on the road – police cars. Despite having a full range of conspicuity enhancers (reflective and retro-reflective materials, flashing lights, cones) stationary police cars have been hit by drivers who subsequently claimed that they did not see them. In these cases it is hard to believe that the individuals’ senses failed to register the police car, but something has gone wrong after the initial registration. The police car, while having high sensory conspicuity, has low attention conspicuity for those individuals. Langham et al. were interested in establishing just what factors of the situation or the individual (or the interaction between them) would be likely to lead to LBFS accidents. To do this, they gathered survey data from a variety of sources, obtaining details of 29 vehicle accidents. This survey identified a number of interesting aspects of LBFS accidents that will now be considered in relation to the discussion above on the role of knowledge in perception. The factors that seemed to be important in LBFS accidents were: 1. There were more accidents when the police vehicle was parked ‘in-line’ (stopped in a lane and facing in the same direction as the prevailing traffic flow) than when it was parked ‘in echelon’ (parked diagonally across a lane). It is easy to speculate that the orientation of the car may influence the perception of that car. Experience tells us that most cars that we see on a road have the same orientation as the other cars and, crucially, that they are moving. Thus a car parked in-line may well be perceived as a moving car – until it is too late. There is much less ambiguity with a car that is parked in echelon; it is an unusual (or even impossible!) orientation for a moving car, and so it is perhaps much more likely to be perceived as stationary. 2. Deployment of warning signs and cones did not guarantee detection. The deployment of such aids would almost certainly raise the sensory conspicuity of the police car still further, but not enough to prevent an accident.

Key Term Visual search Experimental procedure of searching through a field of objects (`distractors’) for a desired object (`target’).

39

40

Chapter 2 | Perception 3. Although the accidents usually occur on motorways and dual carriageways, 62 per cent of the accidents were close (within 15 km) to the perpetrators’ homes. Again, it is possible that this finding is the result of experience. Drivers are familiar with the environment and the roads around their home. They may have driven the same route every day for years – and never seen a police car parked in the road. Thus, when they do see a stationary police car, they assume it is moving, with disastrous consequences. 4. The offenders were all, except one, over the age of 25. As discussed above, this is highly unusual as it is usually the younger drivers that are more likely to be involved in accidents. The finding emphasises the role that knowledge and experience are likely to play in these accidents. More experienced drivers have learnt that cars on the motorway are nearly always moving, and so do not pay sufficient attention to cars that are not moving. It seems highly likely that they detect them, but they do not perceive them appropriately. It would thus appear that one explanation for LBFS accidents is that more experienced drivers are placing more reliance on what they already know and this is affecting what they perceive (or do not perceive). Edgar et al. (2003) have also demonstrated that an overemphasis on using prior knowledge to guide perception may underlie serious accidents referred to as ‘friendly fire’ in which the military open fire on their own side (or on civilians) believing them to be the enemy, even though there are plenty of sensory cues to suggest that they are not (as illustrated in Figure 2.16).

Figure 2.16 Vehicles that had earlier been carrying members of a BBC TV team, hit by ‘friendly fire’ from an aircraft in the 2003 Iraq war. The pilot apparently believed that he was attacking enemy forces that were nearby. Note the clear markings on the side of the vehicle (and the top of the vehicle was also marked). Source: http://news.bbc.co.uk/1/hi/in_depth/photo_gallery/3244305.stm.

THE INFLUENCE OF TOP-DOWN PROCESSING: AN EXAMPLE

There appear to be numerous, not to mention dramatic, examples of what we know influencing what we perceive. To try and drive (excuse the pun) the message home and to allow you to experience a clear example of knowledge influencing perception, have a look at Figure 2.17. What do you see? It is most interesting if you just see a pattern of light and dark shapes. Does it change your perception of the picture if you are told that it is, in fact, a picture of a cat? If you could not see the cat initially but now can after being provided with extra information about the picture, then this is a clear example of knowledge influencing perception. If you still cannot see the cat, have a look at the

2.2 Visual perception picture at the end of this chapter, which should give you even more information about where the cat is. The sensory aspects of the original picture have not changed at all. It is still a collection of light and dark blobs. What has changed is what you know about the picture, and this has changed your perception of it. Even if you did see the cat immediately, your perception of it will be forever changed (hopefully) by knowing that it has been used as an illustration in a textbook.

THE CONSTRUCTIVIST APPROACH: PERCEPTION FOR RECOGNITION From the examples discussed above, and from your own experience, it should now be clear that what we know has huge (and sometimes detrimental) effects on what we perceive, even sometimes overruling apparently clear sensory information that may be telling us something different. Truly, ‘We see things not as they are but as we are’. The next issue to consider is just why we make so much use of stored Figure 2.17 What do you see? knowledge. Given that the consequences of using what we (Answer at end of chapter.) know can sometimes be somewhat detrimental, perhaps it would be better not to use it to such an extent. So why does stored knowledge appear to have such an influence on perception? One of the theories of the way in which perception operates and which deals explicitly with why we make so much use of stored knowledge is the constructivist theory which was initially proposed by Irvin Rock (1977, 1983) and Richard Gregory (1980). It is called a constructivist theory because it is based on the notion that it is necessary for us to ‘construct’ our perception of what we see Key Term from incomplete sensory information. Thus we use what we already know to fill in the gaps and interpret the sensory information Constructivist coming in. In order to do this Gregory suggests that we act as approach ‘scientists’, generating perceptual hypotheses (predictions) about Building up our what we may be seeing and testing those hypotheses against the perception of sensory information coming in. The cat picture used previously can the world from be used again to give an idea of how this works. The picture is not incomplete at all clear and may be difficult, at first, to resolve into anything that sensory input. See makes sense. You might thus generate a range of hypotheses about also ‘perceptual what it may be (horse, cow, battleship, chair, duck) which you can hypotheses’. then check against the sensory information: ‘It looks as though it Perceptual has ears, so the hypothesis that it is a battleship is probably wrong.’ hypotheses Of course the process is not seen as occurring that consciously or An element of that explicitly, but that is the general idea. Once the hypothesis fits the constructivist the sensory information, the image is then recognised, hopefully approach, in which correctly. The constructivist theories thus emphasise a strong hypotheses as to the interaction between sensory information moving ‘bottom-up’ (see nature of a stimulus Chapter 1) and knowledge moving ‘top-down’. The interaction of object are tested the two determines what is perceived. against incoming As we have already seen in this chapter, however, the end result of sensory information. the perceptual process may be wrong (as with the Müller-Lyer illusion).

41

42

Chapter 2 | Perception

Figure 2.18 The faces of Einstein. The left-hand view of the mask is from the front showing a ‘normal’ convex face. Even though the righthand panel shows a ‘hollow’ face (with the nose going away from you) the percept is of a normal face. Source: Photographs courtesy of Graham Edgar.

Gregory, in particular, has demonstrated that we can perhaps learn as much about the perceptual processes when things go wrong as when they go right. Once again, when things go wrong, it seems to be previous knowledge that is to blame. Gregory uses a nice demonstration that illustrates this point (Gregory, 1970, 1997). Look at the faces in Figure 2.18. The figure is a hollow mask of Einstein with the view from the ‘normal’ (convex) side on the left of the figure and the view from the (concave) back on the right. Under certain viewing conditions, whichever view of the mask we take, it still looks like a solid face – not a hollow face. Gregory suggests that this is because we are very familiar with faces as visual stimuli and we are used to seeing ‘normal’ faces with the nose sticking out towards us. A hollow face is a very unusual visual stimulus and we appear very resistant to accepting the hypothesis that what we are viewing is a face that is essentially the spatial ‘negative’ (the bits that normally stick out now go in) of those that we are used to. Although we can, at times, perceive the face as hollow, we are heavily biased toward seeing it as a ‘normal’ face. Some evidence for this perception being based on acquired knowledge is provided by studies (Tsuruhara et al., 2011) that suggest that infants (5-8 months) appear less likely than adults to see a hollow face as ‘solid’. If what we know seems to have so much impact on what we perceive and, apparently, lead to so many errors (as discussed above), then the obvious question is, ‘Why do we make so much use of what we already know in driving our perception of the world?’. It only seems to lead to trouble, so why not ignore what we already know? Apart from the obvious answer that we would not even be able to recognise our own grandmother, there are other reasons for involving knowledge in the process of perception. We have already touched on a possible answer when we first considered the constructivist theory. This is the notion that the sensory input is rather impoverished, and we need to ‘construct’ our perception aided by what we already know to make best use of the rather limited information coming in. The incoming information is limited in two ways. One way has been considered in Chapter 1 (and will be covered in much more detail in Chapter 3) and this is that our cognitive resources can only cope with a certain amount of incoming information, so that a proportion of it is filtered out by our attentional

2.2 Visual perception

43

processes. Another factor limiting the completeness of the incoming sensory information (as already mentioned) is the fact that our senses may not provide a full picture in the first place. This is illustrated by the lower part of Figure 2.19. Our visual acuity is not constant across our field of view and the scene in the upper picture has been progressively blurred in the lower picture to represent the effect of the reducing acuity of the eye with increasing distance from the high-acuity centre (the fovea). What this means is that much of the visual information coming in is actually of quite poor quality. Thus the constructivist theory seems to be making a reasonable assumption in proposing that we need to use prior knowledge to help us to interpret the rather blurry image that we receive from our retina.

EVIDENCE FOR THE CONSTRUCTIVIST APPROACH: MASKING AND RE-ENTRANT PROCESSING Although using stored knowledge to aid in the interpretation of incoming Figure 2.19 Demonstrating what we really see (below) as information is likely to make object opposed to what we feel we see (above). recognition better and faster, the iterative Source: Photograph courtesy of Graham Edgar. Photographic process of generating hypotheses and manipulation by David Brookes. testing them is going to take a certain amount of time. This is not a problem if the incoming sensory information remains constant (or if the observer is, at least, continuing to look at different bits of the same object), but what happens if it changes? The hypothesis testing constructivist approach would predict that a sudden change in the visual input would disrupt processing Key Term and make it more difficult to recognise an object, and this appears to be exactly what happens. Di Lollo et al. (2000) demonstrated that Visual masking changing one stimulus rapidly for another disrupted processing of Experimental the first stimulus, a process referred to as masking. A typical target procedure of following stimulus and mask are shown in Figure 2.20. In a masking paradigm, a briefly presented a second stimulus can prevent recognition of an earlier stimulus if the stimulus by random mask follows very soon after presentation of the stimulus. It is not visual noise or even necessary for the stimulus and mask to be at the same position fragments of other in the visual field (i.e. not spatially coincident). A mask that surrounds stimuli. Interferes with the stimulus (as in Figure 2.20) but does not appear in the same place or interrupts visual can be effective in blocking recognition of a target (Enns and Di Lollo, processing. 2000).

44

Chapter 2 | Perception

Enns and co-workers (Enns and Di Lollo, 2000; Di Lollo et al., 2000) suggest that the mask is effective because it disrupts re-entrant processing. This term is used to describe the finding in neuroscience research that communication between different areas of the brain is never in one direction only. If a signal goes from one area to another, then there is Target Mask sure to be one coming back the other way (Felleman and Van Essen, 1991). Thus the flow Figure 2.20 A target and mask of the type used by Enns and Di Lollo (2000). of information diagrammed in Source: Adapted from Enns and Di Lollo (2000). Figure 2.13 could conceivably be a high-level representation of hypothesis testing using re-entrant processing. Indeed, masking could be conceptualised as drawing attention away from the initial target stimulus so that cognitive resources are no longer allocated to processing it. Key Term Certainly, masking provides support for the constructivist approach. Hupe Re-entrant et al. (1998) suggest that re-entrant processing could be the basis of the processing hypothesis testing postulated by Gregory. Incoming sensory information Information flow (flowing bottom-up) is used to generate an initial hypothesis. The accuracy between brain regions of this hypothesis is then checked against the continuing sensory input (bidirectional). using re-entrant pathways (flowing top-down) and the hypothesis can then be modified and rechecked. The constructivist theory of vision is thus very appealing, elegantly combining bottom-up and top-down processing. One slight puzzle remains, however. If this approach is so good, why does it make so many mistakes? Much of the evidence used to support the constructivist approach, as already discussed, comes from examples of where it goes wrong and visual illusions such as the Müller-Lyer are good examples. Given that it seems to be so easy to ‘fool’ the perceptual system, why aren’t such things as LBFS accidents far more common? They are, thankfully, quite rare. One criticism of the constructivist approach is that previous knowledge appears to be so important due to the kinds of methods and stimuli used to test perception. Many investigations of perception are done in the laboratory using deliberately simple, and often static, stimuli. Thus, the sensory input is a very impoverished version of what an individual would normally be exposed to in the real world. Some of the stimuli used to illustrate the use of knowledge are even deliberately difficult to recognise, such as the cat picture in Figure 2.17. Thus, it could be argued that if you ask people to view a static two-dimensional, impoverished, image under laboratory conditions, you will force them to use knowledge to try and make sense of it. If you allow people to move around in the world, with a rich flow of sensory information coming in and changing as the individual moves and looks around (and as objects in the world move around

2.2 Visual perception

45

them), then it is possible that far less top-down information will be needed – or perhaps none at all! Thus the lower picture in Figure 2.19 only looks so poor because it represents what the world would look like if we were unable to move our eyes, or ourselves.

THE GIBSONIAN VIEW OF PERCEPTION: PERCEPTION FOR ACTION The notion that studying perception in artificial conditions in a laboratory will give rise to false conclusions of how the system works was a notion championed vigorously by J.J. Gibson (1950, 1966). Gibson, rather than considering how perception operates, was much more concerned with what perception is for. That is, Gibson proposed that perception should be considered in terms of how it allows us to interact with the world we live in. Gibson’s approach may be summed up by the term ‘perception for action’. In the theories of Gibson there is a strong link between perception and action with perception being referred to as direct. The basis of direct perception is that the sensory information available in the environment is so rich that it provides sufficient information to allow a person to move around, and interact with, the environment without the need for any top-down processing. Gibson would claim that the results obtained in laboratory studies are misleading in that they are studying indirect perception of static 2-D representations of the world. That is, laboratory studies (and visual illusions) do not demonstrate how we interact with the world, merely how we react to impoverished representations of it. For Gibson, moving within the environment and interacting with the environment are crucial aspects of perception. As Gibson (1979) put it, ‘perceiving is an act, not a response’. One problem, of course, with denying the use of stored knowledge in perception is that it becomes rather difficult to work out how we can interact with objects in the world without recognising them in the way that would be proposed by the constructivist approach. Gibson (1979) developed his theories by suggesting that we are able to interact with objects in the world because they afford their use. For instance, consider Figure 2.21. It is a picture of a hammer, and Gibson would suggest that a hammer would afford hitting things. If you think this is an unreasonable assumption, try giving a hammer to a two-year-old who has never seen a hammer before, and see what they do with it. Actually do not try that, although it would almost certainly be a good example of an object affording its use.

Key Term Direct perception Perception without the need for top-down processing.

EVIDENCE FOR THE GIBSONIAN APPROACH Although Gibson’s theories may seem a little unreasonable there is evidence that at least some part of the perceptual

Figure 2.21

What do you do with this?

Source: Photograph courtesy of Graham Edgar.

46

Chapter 2 | Perception process may act in a ‘Gibsonian’ manner. Handy et al. (2003) presented participants with pictures of two task-irrelevant objects while they were waiting for a target to be presented. One of the pictures was of a tool and the other was of a non-tool. Objects that could be grasped (such as hammers) drew attention and functional magnetic resonance imaging (fMRI) of brain function indicated activity in dorsal regions of premotor and prefrontal cortices. Also, as suggested by Bruce et al. (1996), direct perception would make sense in terms of instinctive, visually guided behaviour. For example, if a frog were trying to snare a fly with its tongue, it is not necessary for the frog to ‘know’ anything about flies, or even to recognise the small buzzing object as a fly. All it needs to do is to sense the small flying object and use that sensory information to guide its tongue to allow it to snare it (although it could be a nasty surprise if it is not a fly). Thus the constructivist and Gibsonian theories seem to conflict, one emphasising the centrality of stored knowledge in the perceptual process, the other denying that it is necessary at all. The question, of course, is which one is right? Well, it is not giving too much away to say that it looks as though both theories could be right and that both types of processing could be occurring in perception. To illustrate this, we shall have a look at the structure of the visual system.

THE STRUCTURE OF THE VISUAL SYSTEM

Key Term Ventral stream A pathway in the brain that deals with the visual information for what objects are. Dorsal stream A pathway which carries visual information about the spatial location of an object.

Even very early in the visual system there appear to be (at least) two distinct streams of information flowing back from the retina (Shapley, 1995). These streams are referred to as the parvocellular and magnocellular pathways (e.g. Shapley, 1995), the names deriving from the relative sizes of the cells in the two pathways. These pathways carry information back to the primary visual cortex. You may already have an idea of where your visual cortex is if you have ever been hit on the back of the head (where the visual cortex is) and ‘seen stars’. A blow to the back of the head can lead to spontaneous firings within the visual cortex – and the impression of ‘stars’. After the visual cortex, the visual information is still maintained in (at least) two distinct streams (see Figure 2.22). One stream is termed the ventral stream and leads to inferotemporal cortex and the other, leading to parietal cortex, is known as the dorsal stream.

THE DORSAL AND VENTRAL STREAMS While heavily interconnected and apparently converging in prefrontal cortex (Rao et al., 1997), the dorsal and ventral streams seem to be specialised for different functions and to have different characteristics. For instance: 1. The ventral stream is primarily concerned with recognition and identification of visual input whereas the dorsal stream provides information to drive visually guided behaviour such as pointing, grasping, etc. (Ungerleider and Mishkin, 1982; Goodale and Milner, 1992).

2.2 Visual perception

47

Parietal cortex

rs

Do al str m

ea

ral

t Ven

am

Primary visual cortex (V1)

stre

Inferotemporal cortex

Figure 2.22 The dorsal and ventral streams. Source: Drawing courtesy of David Groome.

2. The ventral system is better at processing fine detail (Baizer et al., 1991) whereas the dorsal system is better at processing motion (Logothesis, 1994), although the differences are only relative as, for example, the ventral system can still carry motion information. 3. The ventral system appears to be knowledge-based using stored representations to recognise objects whilst the dorsal system appears to have only very short-term storage available (Milner and Goodale, 1995; Bridgeman et al., 1997; Creem and Proffitt, 1998). 4. The dorsal system is faster (Bullier and Nowak, 1995). 5. We appear to be more conscious of ventral stream functioning than dorsal. For instance individuals may report awareness of ventral processing, while manifesting different dorsal processing. A good example of this is if people actually interact with visual illusions, such as the hollow-face illusion (Ho, 1998; Króliczak et al., 2006). The perception is illusory, but the action (e.g. flicking a fly off the nose of the hollow face) does not appear to be influenced by the illusion. This difference in dorsal and ventral processing will be discussed in more detail below. 6. The ventral system aims to recognise and identify objects and is thus object-centred. The dorsal system is driving some action in relation to an object and thus uses a viewer-centred frame of reference (Goodale and Milner, 1992; Milner and Goodale, 1995). These characteristics support earlier research (Schneider, 1967, 1969) which suggested that the ventral stream is concerned with the question, ‘What is it?’ whereas the dorsal stream is concerned

48

Chapter 2 | Perception with the question, ‘Where is it?’ Thus, the ventral pathway is often known as a ‘what’ system, and the dorsal pathway a ‘where’ system (Ungerleider and Mishkin, 1982). Norman (2001, 2002), following on from similar suggestions by Bridgeman (1992) and Neisser (1994), has suggested a dual-process approach based on the characteristics of the two streams outlined above. In this approach, it is suggested (Goodale and Milner, 1992) that the dorsal and ventral streams act synergistically, with the dorsal stream largely concerned with perception for action, and the ventral stream with perception for recognition. The function and characteristics of the two streams thus seem to fit rather nicely with the two theories of perception outlined above, with the dorsal stream appearing rather Gibsonian in the way that it operates, and the ventral stream rather constructivist. Thus, we appear to have a fast system ideally suited for driving action, but which makes relatively little use of stored information (the Gibsonian dorsal stream) combined with another slower system that uses stored knowledge to analyse fine detail and recognise objects (the constructivist ventral stream). A rather elegant study conducted by Króliczak et al. (2006) demonstrated the different modes of operation of the two streams. The study used a hollow face like the one in Figure 2.18. Participants were asked to estimate the position of targets placed on the hollow (but phenomenologically normal) face and then to use their finger to make a rapid motion to ‘flick’ the target off. Even though participants still saw the illusion of the face as solid and coming toward them, the flicking movements were directed to the ‘real’ position of the face; that is ‘inside’ the hollow face. The authors suggest that the ventral stream maintains the perception of the face as ‘solid’ (as it is fooled by the illusion) whereas the dorsal stream drives the flicking action and is not fooled. It is rather apt that, considering Gregory used illusions to illustrate the constructivist approach, that the ‘constructivist’ ventral stream ‘sees’ the illusion, whereas the Gibsonian dorsal stream apparently does not – especially as Gibson regarded visual illusions as mere artefacts of using unrealistic stimuli.

THE INTERACTION OF THE DORSAL AND VENTRAL STREAMS: PERCEPTION FOR RECOGNITION AND ACTION

Key Term Phenomenological experience Our conscious experience of the world.

Of course, just because the two streams appear to process the hollow face independently, it does not mean that the streams do not interact. It is interesting to speculate, as we finish this discussion of visual perception, just how these two types of processing may act together to allow us to perceive our world. To do this, it is worth considering our experience and consciousness of what we are perceiving, i.e. our phenomenological experience. The founder of the phenomenological tradition was a German philosopher-mathematician called Edmund Husserl (1931) who suggested the concept of intentionality, whereby the mind reaches out to the stimuli that make up the world and interprets them in terms of our own personal experience, which

2.2 Visual perception is a theme that has been developed throughout this chapter. As an example of this, consider once more the pictures in Figure 2.19. At any one moment the sensory information coming in from the world gives us a view of the world rather like that in the lower picture. Our phenomenological experience of the world, however, is more like that of the upper picture. We have the impression that we have a clear and accurate perception of the world surrounding us at any one time. An analogy for this is the light in your refrigerator (Thomas, 1999). It always appears to be on because whenever you go to the fridge and open the door, the light is on (the irreverent magazine Viz once suggested that it would be a good idea to drill a hole in the door of your refrigerator so you can really be sure that the light does go off when you close the door!). The experience of the real world is much the same. Whenever you look at any object in the real world it appears clear and sharp (assuming your eyesight is good) because as soon as you become interested in some part of the visual world, you tend to move your eyes so that the image of that part falls on the high-acuity central region of the retina. Thus, you tend not to be aware that the rest of the time that part of the world is just a blur (in the same way that you never see the refrigerator light off). Stored knowledge allows us to maintain this phenomenological percept that the world is sharp and clear. Having looked at something, we can remember it as sharp and clear, even when we look away and the sensory information coming from that information is actually blurred. Essentially, we could build up an internal ‘model’ of the world around us at any time using our knowledge. This is not to suggest that we do have a little ‘model’ of the world inside our heads (although a template-matching model would certainly suggest that we have bits of it). We don’t really need it as we can use our environment as an ‘external memory’ (O’Regan, 1992) that we can recall at any time just by looking around. The constructivist ventral stream would seem to be ideal for building up, and maintaining, our representation of the world, recognising objects as they appear in central vision and generating stored representations of those objects for when we are looking elsewhere. As long as everything remains unchanged, our perception of the world should be fairly accurate. To maintain that accuracy, however, we need a system that will warn us if some part of the visual world changes. This is one of the functions that the dorsal stream could serve. Just as the ventral stream appears to be ideally suited for recognising objects, so the dorsal stream appears to be well suited to detecting change in the visual world (e.g. Zeki, 2003). Beck et al. (2001) demonstrated this function of the dorsal stream using a paradigm in which participants viewed (sequentially) two images of a face or a scene. Sometimes the two images were the same, and sometimes the second image had been changed in some way. A blank screen was presented between the two face/scene images to avoid participants simply detecting any ‘flicker’ caused by the change. Functional magnetic resonance imaging (fMRI) was used to examine the different brain activity when subjects noticed the change (change detection)

49

50

Chapter 2 | Perception as opposed to when they missed the change (change blindness). Beck et al. (2001) found enhanced activity in the parietal lobe (an element of the dorsal stream) when subjects were conscious of a change, but not when the change went unnoticed. Of course, fMRI studies of the sort conducted by Beck et al. only reveal an association between a region of brain activity and some behaviour on the part of the individual. Beck et al. (2005), however, used repetitive transcranial magnetic stimulation to disrupt activity in the right parietal cortex and found that the ability to detect changes in a visual stimulus was disrupted (no effect if the left parietal cortex was disrupted). There thus appears to be evidence that the dorsal stream is, indeed, well suited to a role of detecting change in the environment, so that the ventral stream can then be brought into play to see what has changed and how. Given the evidence presented so far, there seems to be a rather elegant division of function in perception between ‘perception for recognition’ and ‘perception for action’, and this split in perception is supported by two functionally distinct processing streams in the brain, the dorsal and the ventral. It seems almost too simple to be true and, unfortunately, that may be the case. Singh-Curry and Husain (2009) suggest that the inferior parietal lobe (right hemisphere), amongst other functions, responds to salient new information in the environment. This response fits in well with one of the suggested roles for the dorsal stream; that of signalling the appearance of change. Singh-Curry and Husain, however, suggest that the inferior parietal lobe is not a part of either the, ‘traditional’ dorsal or ventral streams, and suggest that the original dorsal/ventral dichotomy is rather simplistic. Thus we need to bear in mind (excuse the pun) that the simple dorsal/ventral distinction may need to be tweaked a bit. For the moment, though, we can accept that no matter how many streams there may be, between them they can handle ‘perception for recognition’ and ‘perception for action’. Thus, to return to the question earlier in this chapter, it may not be necessary to get out of your car every time you come to a sharp bend. If there is something unexpected around the corner, your visual system will probably detect it, recognise it, and guide your action appropriately – most of the time.

2.3 AUDITORY PERCEPTION So far we have only considered one of the senses – vision. As we shall see (or hear!), there are many others, although perhaps the most researched sense after vision is that of hearing. Our sense of hearing serves many functions, not least in allowing us to hear speech. There is, however, insufficient space to consider the complexities of speech perception in this chapter, and good introductions to speech perception are provided in Banich and Compton (2010) and Goldstein (2009). This section will therefore consider the role of hearing in an area that we have already discussed: detecting change in the environment. Any sound occurring in the environment will, by definition, be the result

2.3 Auditory perception

51

Figure 2.23 Sound localisation in the horizontal plane. Sounds to one side of the head will reach the nearest ear sooner and tend to sound louder in that ear. Individuals can use these cues to localise a sound and so orient towards it. Source: Photographs courtesy of Graham Edgar.

of some change. To produce the transient changes in air pressure that form sound waves, something must have changed, even if only by a small amount. Thus one of the functions of our auditory system is to detect sounds resulting from changes in the environment and to give some indication of where those sounds are occurring. A discussion of auditory localisation is useful here, in that it emphasises particularly strongly that the senses do not operate independently, but act synergistically to allow us to perceive the world around us.

AUDITORY LOCALISATION Auditory localisation is usually described using the following three coordinate systems: 1. Azimuth (horizontal), determined primarily by binaural cues, specifically time and intensity differences between stimuli reaching the left and right ears (see Figure 2.23). Interaural intensity differences are largely due to the shadowing effect of the head that keeps high-frequency sounds from reaching the far ear. Long wavelengths (low-frequency sounds) are unaffected by the head, but shorter wavelengths (high-frequency sounds) are reflected back. This feature has been shown to be surprisingly useful in an evolutionary perspective. As a general rule, animals with smaller heads are sensitive to higher frequencies. Pheasant chicks have evolved a chirp that exploits this feature. The chicks emit chirps at roughly the same wavelength as a fox’s head width, thus making it very difficult for their main predator to locate them by sound, whereas the chicks’ mother (having a smaller head than a fox) can locate them easily (Naish, 2005). 2. Elevation (vertical), determined mainly by spectral cues which are generated by the way in which the head and outer ears (pinnae) affect the frequencies in the stimulus. Sound reflected from the pinnae can be used to give an idea of the elevation of a sound. Thus the pinnae play an active role in sound localisation, suggesting that they did not evolve solely to rest spectacles on. If you fill in the pinnae with modelling clay (do not try this at home, although if

Key Term Binaural cues Cues that rely on comparing the input to both ears, as for example in judging sound direction. Spectral cues Auditory cues to, for example, distance provided by the distortion of the incoming stimulus by (e.g.) the pinnae (ear lobes).

52

Chapter 2 | Perception you give the modelling clay to the two-year old that you gave the hammer to in Section 2.2, they will probably stick it in their ears without being asked; modelling clay is also likely to afford its use), sound localisation progressively worsens (Gardner and Gardner, 1973). Sound can also be reflected back off the torso (‘shoulder bounce’). 3. Distance coordinate (how far a sound source is from the listener). Generally, judgements of distance for sounds within an arm’s length are good (interaural level difference (ILD) is large), but as sounds get further away, distance judgement is much more difficult, and distance to far-away sounds is generally underestimated. There are several mechanisms for auditory far-distance judgement, which are used together to determine perception of a sound’s distance (much as with visual distance cues); they include: r
Sound level – just as light sources that are further away appear dimmer due to scattering and absorption of the light by the intervening atmosphere (assuming you’re not in space of course), doubling the distance of a sound source can reduce sound pressure level (SPL) by around 6 dB (outside in the open with no echoes) – or to about a quarter of its original level. It is difficult, however, to make a judgement of distance based on sound pressure intensity without some prior knowledge of how loud the source should appear at different distances. Therefore the listener needs to be familiar with the sound source (e.g. a voice) or be making a comparative judgement of the distance of two identical sources. r
Frequency – short (blue) wavelengths of visible light tend to be more strongly absorbed and scattered by the atmosphere, and so the more atmosphere the light has to travel through, the redder it will appear (this is why sunsets and sunrises tend to appear reddish). Similarly, high frequencies of sound undergo more attenuation by the atmosphere than low frequencies. Sounds that are further away, therefore, become more dull and muffled. r
Motion parallax – see Figure 2.24. Nearby sounds appear to shift location faster than sounds that are further away. This is analogous to the visual depth cue of motion parallax. r
Reflection – Sound can reach the ears in two ways: – direct sound: an uninterrupted path from source to ear; – indirect sound: sound that is bounced off (reflected by) objects, e.g. walls or ground. As distance increases, so does the ratio of indirect to direct sound and the change in sound quality provides a distance cue. The differences in auditory processing result in differences in the accuracy with which the human listener can place sounds along these axes. Localisation accuracy is generally lower for elevation sources than for sources that differ in azimuth (Middlebrooks, 1992). Listeners can localise sounds directly in front of them most accurately (errors average 2–3.5) and sounds that are off to the side and behind the head

2.3 Auditory perception

53

Figure 2.24 Motion parallax. Moving sound stimuli that are closer will tend to shift location with respect to the listener faster than those that are further away. The same is true for visual stimuli. Source: Drawing by Helen Edgar.

least accurately (errors up to 20). For further discussion of auditory localisation acuity see Oldfield and Parker (1984a, 1984b). One question of course is that, given there appears to be a processing stream (or streams) within the brain specialised for working out where visual stimuli are, is there a similar stream for auditory stimuli? The answer, unsurprisingly, is that there appears to be just such a stream (for a review of the evidence see Rauschecker and Scott, 2009) The postero-dorsal stream runs from primary auditory cortex to the parietal lobes (and then to the frontal lobes). It was originally proposed (Kaas and Hackett, 1999) that this postero-dorsal stream was involved in localising sounds, serving a function analogous to the original conceptualisation of the visual dorsal stream as a ‘where’ stream. Also, like vision, it is now suggested (e.g. Hickok and Poeppel, 2004, 2007) that the postero-dorsal auditory stream provides an interface with the motor system and is involved in, amongst (many!) other things, speech production, which would imply that the postero-dorsal stream is also a ‘perception for action’ stream (Hickok and Poeppel, 2007). As you might expect, if there is a ‘perception for action’ stream in audition, there is also likely to be a ‘perception for recognition’ one too, and indeed this does seem to be the case. There is an anteroventral stream running from primary auditory cortex to the temporal lobes and, again on into the frontal lobes. The role of this pathway appears to be similar to that of the visual ventral stream, and involves auditory object identification and speech perception (e.g. Hickok and Poeppel, 2007; Rauschecker and Scott, 2009). Much of the work on auditory processing has concentrated on how a listener (often with fixed head position in a quiet room or an anechoic chamber) can hear sounds, and some interesting problems have been highlighted. For instance, for auditory stimuli that are

54

Chapter 2 | Perception equidistant from the two ears, confusion can occur as to whether the source is in front of or behind the observer. For most situations in the real world, however, the listener will be able to move freely and will have visual (and other) cues available that can be used to resolve any ambiguity. Under real-world conditions the sensory systems work together and accurate predictions of real-world responses are difficult to measure or generalise when considering, for example, the auditory system in isolation. So far, we have focused on vision and audition, and it can be seen (or heard!) that the auditory and visual systems interact in many ways to influence our final percept. For example, Vroomen and de Gelder (2000) demonstrated that the perceptual organisation of sound affects visual scene analysis. Links between auditory and visual systems can occur at the low-level bottom-up stages (Vroomen et al., 2001), or through the influence of higher cognitive processes (top-down) such as the prior expectations of a participant (Egeth and Yantis, 1997). Sedda et al. (2011) found that, if participants heard the sound of a wooden block being placed on a table, it affected their grip aperture when they reached for it – whether or not they were able to see it as well. The participants appeared to be using auditory cues, and previous knowledge (such as what sound a block of wood of a certain size makes when it hits a table) to assist in their reaching, and these auditory cues were still utilised when visual cues were also present. When considering the cognitive psychology of auditory perception, it is therefore advisable to remember that, although a single aspect may be studied in order to isolate factors for investigation, these factors rarely act alone in the real world. Interactions can lead to rather different results to those found in the laboratory, for example improved auditory localisation with visual cues. Cross-modal studies of auditory localisation have demonstrated that visual cues can improve the accuracy of auditory localisation both in azimuth and elevation, provided that the visual cues are congruent with the auditory stimulus (an inconsistent or mismatched visual cue is worse than no cue). The McGurk effect, where a listener hears a completely new sound ‘da’ when viewing mismatched lip movements ‘ga’ and sound ‘ba’ from a monitor, could be considered as an extreme example of incongruent auditory and visual stimuli. In addition the type of visual stimulus will affect the degree of improvement. If the visual stimulus strongly matches the auditory stimulus, then participants perform more accurately. Thus if the visual stimuli are speaker icons, then performance is better than if a simple card marks the possible sound sources. Also, visual facilitation of auditory localisation is better if the source locations are marked with objects placed in actual 3-D positions, rather than represented on a 2-D grid. Auditory localisation performance is therefore improved if an auditory stimulus is accompanied with a meaningful (congruent) visual cue (Saliba, 2001). These findings demonstrate once again the influence of knowledge on perception. For instance, we know that there has to be a source for a sound – such as a loudspeaker.

2.3 Auditory perception

AUDITORY ATTENTION Unlike our eyes, our ears cannot be directed to avoid registering material that we wish to ignore. In a busy setting we are swamped with simultaneous sounds. Principles of auditory grouping analogous to the Gestalt laws of visual perception can be utilised to solve this problem and help direct auditory attention to differentiate ‘signal’ from ‘noise’ and separate superimposed sounds: r
Location: Sounds created by a particular source usually come from one position in space or move in a slowly changing and/or continuous way (e.g. a passing car). r
Similarity of timbre: Sounds that have the same timbre are often produced by the same source, i.e. similar sounding stimuli are grouped together. r
Sounds with similar frequencies are often from the same source. r
Temporal proximity: Sounds that occur in rapid progression tend to be produced by the same source. Treisman and Gelade (1980) suggest people must focus attention on a stimulus before they can synthesise its features into a pattern. This applies not only for visual stimuli, but also for auditory stimuli … you must focus your attention on complex incoming information in order to synthesise it into a meaningful pattern. Thus, meaning is also important for deciding where an auditory stimulus is and whether it will be processed to the level of perception.

INTERACTIONS AND REAL-WORLD EXAMPLES There is an important distinction between reductionist laboratorybased research and more applied areas such as auditory display research (Walker and Kramer, 2004). Psychophysical experiments that isolate particular aspects of a stimulus provide fundamental background information (from a carefully controlled environment) about how sound reaches the ears and how it is sensed. This approach, however, is just a starting-point for the study of auditory perception. Concentrating upon individual aspects of the (auditory) system and not the interactions that lead to the final percept can lead to some interesting (and expensive) problems.

Example – concert theatre design The optimum reverberation time for a concert hall is considered to be 2 seconds. The New York Philharmonic Hall, which opened in 1962, was designed to replicate this single factor of ‘ideal reverberation’. Despite achieving a reverberation figure very close to the ‘ideal’, the musicians could not hear each other and the acoustics were obviously not as expected. This culminated in a complete rebuild of the interior. Current practice uses multiple measures, e.g. intimacy, spaciousness, timbre and tone colour (Beranek, 1996). The current approach recognises what has been termed a more ecological approach and attempts to consider the effects of sound as it is heard in the real

55

56

Chapter 2 | Perception world (natural sound). This is more akin to the approach of Gibson, discussed earlier in this chapter.

TOP-DOWN INFLUENCES ON AUDITORY PERCEPTION Key Term Phantom word illusion What we hear may be influenced by what we expect to hear.

A listener’s experience and frame of mind can influence how a message is perceived. Diana Deutsch (2003) demonstrated, with phantom word illusions, that people often report ‘hearing words related to what is on their minds’. The demonstration used simple words, e.g. ‘Boris’, ‘Go back’, ‘Harvey’ played repeatedly and continuously. Listeners reported hearing new words and phrases that were not present in the original recording. As with vision, there is an interaction of top-down and bottom-up processing. A real-world example of how different individuals may extract very different meanings from the same stimulus is given by the following summary adapted from a report in the confidential human factors incident reporting (CHIRP) aviation bulletin of 2005. Public announcement (PA) overload – a personal perspective? r
An early afternoon flight was slightly delayed due to maintenance. r
During boarding the cabin crew twice announced a welcome, apologised for a short maintenance delay and offered the opportunity to purchase scratch cards. r
Those on board tended to ignore the PA and continue to chat or read. r
When all were on board, the Captain made a PA (at a low volume) apologising for the delay. He gave a few details about the trip and asked passengers to pay attention to the safety brief. r
The safety brief was preceded by an announcement about the inflight magazine, gift items and scratch cards. r
The aircraft pushed back and the safety brief commenced. r
Most people continued to chat or read and some revellers in the rear [of the cabin] continued to make a noise. r
The aircraft commenced take off; at the point of rotation (aircraft still on the ground but starting to pitch up) the aircraft lurched quite markedly. r
The aircraft became airborne and all seemed normal again. r
During the climb the cabin crew broadcast a PA about the imminent scratch-card sale. r
After the scratch-card sale was over, another PA informed passengers that snacks, drinks and gift items featured in the magazine would be offered for sale. r
The next PA was from the Captain, again at low volume. He announced details of the weather at the destination, the expected arrival time and a couple of features of interest visible from the lefthand side of the aircraft. r
Again most people were reading, chatting or being noisy. Most were not listening to the Captain’s PA, which had by this stage been on air for a minute or so.

2.3 Auditory perception r
The Captain then proceeded to quietly inform the passengers: ‘Oh by the way, some of you may have noticed a roll on take-off, we may have a problem with the aircraft so just as a precaution we are going to prepare the cabin for an emergency landing.’ r
The emergency brief was delivered by the cabin crew very quickly, but included a demonstration of the brace position (the position that passengers are advised to sit in for an emergency landing). r
There were still a significant number of passengers who were unaware that anything out of the ordinary was going on. r
The cabin crew hurriedly secured the cabin. r
The aircraft descended and there were no further PAs. r
The writer [of the report] was unsure whether or not to adopt brace position. r
The aircraft touched down normally and taxied onto the stand, followed by emergency vehicles. r
The next PA (low volume) came from the Captain, apologising for the emergency preparation and saying, ‘Better safe than sorry.’ r
Almost immediately a cabin crew PA thanked passengers for choosing their airline. After a brief pause the PA continued with information about car hire, bus tickets and hotel offers. r
In the baggage hall, one woman was openly crying, some people were excitedly talking about the incident whilst some seemed unaware that anything untoward had happened. The writer concluded that the constant bombardment of PAs caused people to ‘switch off’ and not listen. ‘If there had been a problem on landing and we did thump and skid across the airfield, there would have been a significant number of passengers who were not prepared for it.’ What is clear from this incident report is that different people came away from the same flight with widely different ideas about what was going on. Some passengers were so upset by the emergency landing, and what they considered to be a narrow escape, that they were reduced to tears, whereas others were totally unaware that there had been an emergency landing. So, how could this happen since they were all ‘listening’ to more-or-less the same auditory stimuli (messages) in the same environment (the aircraft cabin)? To answer this question, it is necessary to consider the aspects of both the stimulus and the listener that might lead to different percepts in different individuals: r
Each individual will not have received exactly the same auditory stimuli. There will have been variations in the level of sound due to the cabin environment. r
The individuals’ mental model of what is going on or likely to happen could influence what they attended to. r
Sensory overload: A listener can be ‘overloaded’ with auditory messages or warnings (Meredith and Edworthy, 1994). In this example there were eleven PAs and two safety briefings containing information on at least twenty different topics.

57

58

Chapter 2 | Perception r
Confusion: Critical information embedded in messages with lots of trivial/irrelevant information (Edworthy et al., 2003).

Key Term Mental model A representation that we construct according to what is described in the premises of a reasoning problem, which will depend on how we interpret these premises. Sensory overload A situation in which there is too much incoming sensory information to be adequately processed.

This example highlights the fact that, just because a stimulus is above threshold and is capable of being ‘heard’ does not mean that the listener will attend to the stimulus or that the information content can be extracted and assimilated into a meaningful percept ready for action. In effect, this is the auditory equivalent of the ‘looked but failed to see’ problem (listened but failed to hear?). In order to study how a listener will respond to a particular auditory stimulus in the real world, be it music in a concert hall or an auditory warning display in a cockpit, it is essential that multiple factors and interactions are considered. After all, humans are not passive listeners in their environment, hearing has a function and that function is usually linked to action. For instance, if a person hears a loud bang, they will have some idea from their auditory system about where that bang has originated, they will probably orientate towards the bang in order to gather additional visual information to improve the accuracy (with which they can localise the source); if they have any previous knowledge of that type of sound, they may move towards the sound (if the mental model is of a two-year-old falling off a chair, possibly while trying to reach the hammer or the modelling clay…) or away from the sound (if the mental model is of a runaway truck approaching). The example of a runaway vehicle highlights another important aspect of how auditory stimuli are perceived in the real world, that is the stimuli are by nature dynamic, transient (e.g. a clap) or changing (the source could be moving, or varying as in speech or music). In many cases the listener will also be moving, for example walking, travelling in a car, or simply turning or nodding their head. Thus, there are a myriad of links between action, vision, hearing and other senses, some of which will be discussed in the next section.

2.4 HAPTIC PERCEPTION MORE THAN FIVE SENSES? It is usual to think of humans as having five senses: vision, hearing, smell, taste and touch. However, can we not also sense whether we are standing upright or leaning forward, and if so, which sense is this? Similarly, if I close my eyes I can sense quite precisely where my arms and legs are, at least with respect to my body and to one another; but what sense am I using? When I touch an object I can discern whether it is smooth or rough, large or small and also whether it is hot or cold, but are all of these worked out using my sense of touch? If so, how is it I can sense the heat from a hot cup of tea as I move my hand above it or that I feel cold as I walk along the freezer aisle at my local supermarket, even though I’m not touching either the tea or the freezers? What about pain; is that the same thing as touch? If it is, am I somehow touching my intestines when I have indigestion? In addition,

3

Colour

3

Radical

3

3

Vision

Accepted

Radical

Light

Sensory modality

Hearing

3

3

3

Mechanoreception

3

Sensory modality

Red

3

Balance

Green

3

Rotational acceleration

Blue

3

Linear acceleration

3

Smell

3 3

2,000 or more receptor types 3

Taste

3 3

3

Muscle strength – Golgi tendon organs

3

Muscle stretch – muscle spindles

3

Salt

3

3

Sour

3

3

Bitter

3

3

Blood pressure

3

Arterial blood pressure

3

3

Kineasthesis

3

3

3

3

3

Touch

3

Proprioception – joint position

Sweet

Umami

59

Conservative

Accepted

Conservative

2.4 Haptic perception

Interoceptors 3

3 3

Central venous blood pressure

3

Head blood temperature

3

Light touch

3

Blood oxygen content

3

3

Pressure

3

Cerebrospinal fluid pH

3

3

Plasma osmotic pressure (thirst?)

3

3

Artery–vein blood glucose difference (hunger?)

3

3

Lung inflation

3

3

3

Pain

3

Cutaneous

3

Somatic

3

Visceral

3

Temperature

3

Heat

3

3

Cold

3

3

Figure 2.25

Bladder stretch

3

Full stomach

3

Total

How many senses do we have?

Source: Adapted from Durie (2005).

I can somehow sense, for example, whether I am thirsty or hungry and whether my lungs are inflated. From the above, it should be clear that five senses are not nearly enough to encompass the entire spectrum of information that we can detect. So, how many senses do we actually possess? Even excluding such phenomena as a sense of disappointment, a sense of achievement or a sense of belonging, and restricting the definition of a sense to

1 0

2 1

3 3

60

Chapter 2 | Perception detection of a specific form of information by a specific type of sensory cell which in turn is processed by a particular part of the brain, Durie (2005) suggests that there are at least 21 senses, possibly a lot more (see Figure 2.25). It should also be apparent that we have some senses, such as hearing and smell, that are primarily concerned with sensing information coming from our environment, and some senses, such as our sense of pain (we call this ‘nociception’) and senses such as thirst and hunger (which involve specific types of interoceptors) that provide information about the state of our own bodies. Importantly, we can combine cues from these two broad categories of senses (i.e. internal and external senses) to provide more detailed information about the environment around us. For example, even without using my eyes I can determine where objects are and how large they are simply by moving my hands over their surface. In doing this I’m combining information about the relative position of my hands (where they are with respect to each other and my body) with information from the touch receptors in my fingers, that let me know when they are in contact with a surface, to determine exactly where my hands are when they come in contact with the surface. In the rest of this section we will be exploring in more depth how we can perceive the environment using senses such as ‘touch’ and looking at how we combine information from more than one sense.

PROPRIOCEPTION, KINESTHESIS AND HAPTIC INFORMATION

Key Term Proprioception Knowledge of the position of the body and its parts (arms, fingers, etc.). See also ‘haptic perception’.

The sense that keeps track of the position of our body, limbs, fingers, etc. is known as proprioception and it operates through a system of nerve cell receptors (known as proprioceptors) that allow us to ascertain the angle of our various joints. A related sense, known as kinesthesis, allows us to discern how our body and limbs are moving and is a key element in such things as hand–eye coordination, and as such is a sense that can be improved through training and practice. Unfortunately there is considerable variability in exactly what the terms kinesthesis and proprioception are taken to mean (Owen, 1990). For example, Riccio and McDonald (1998) define kinesthesis as the perception of the change in the location of the whole body compared with the environment (thus movement of the whole body is necessary to generate kinesthetic information) and proprioception to mean the perception of where our body parts are in relation to each other and the environment. Proprioception is also sometimes used as a collective term encompassing all the information regarding the position of the body, including kinesthesis and our sense of balance. We will not concern ourselves with debating a precise definition here, but instead will stick to the key point, which is that we are able to sense the position and movement of our bodies and limbs without resorting to looking to see where they are. If you try reaching out (with your eyes closed of course) and feeling an unknown object in front of you, you will quickly realise that to obtain any information that might be useful in recognising

2.4 Haptic perception what the object is, you need to be able to sense when your fingers touch the object (through the touch receptors in your skin) and also where your fingers are when they touch it. As you move your fingers to explore the object, you need to sense whether or not they are still in contact with the object and also how far they are moving. Thus in exploring the environment we need to combine our sense of touch with proprioception and kinesthesis, and in so doing we produce what is referred to as haptic information. Our ability to judge the position and movement of our hands seems to be quite accurate and compares well with the acuity of our visual system (Henriques and Soechting, 2003). There are some elementary judgements that are more accurately performed using visual rather than haptic information; we tend to mistake an inwardly spiralling movement as describing a circle for instance, but on the whole we can judge the geometry of any surface we touch very accurately without recourse to vision (Henriques and Soechting, 2003). Indeed, there is some evidence that the brain uses the same cognitive processes to categorise natural objects (e.g. seashells) regardless of whether the object was identified visually or haptically (Gaissert and Wallraven (2012). However, unlike the visual system, which combines the sensory input from both eyes, there is some evidence that the brain does not work in a similar fashion with regard to the two hands. Squeri et al. (2012) used a robotic manipulation to move the hands of participants along curved contours and asked them to indicate which contour was the more curved. Their results showed that sensitivity was not increased when both hands were moved compared with when just one hand was moved. Instead, the results suggested that the brain uses a process of sensory selection, whereby information from the hand that is ‘motorically dominant’ (usually the right hand) is given preference over the other hand, even though this is often the hand that is more sensitive (usually the left). As you might expect, given how similar our hands are and also our brains, there appears to be great similarity in how people explore the environment in order to generate haptic information. Klatzky et al. (1987) reported that their participants tended to employ a consistent series of exploratory procedures when asked to explore an object using their hands. Lederman and Klatzky (1990) found that each particular exploratory procedure seemed to be used in order to determine a specific aspect of the object, so that unsupported holding was used to ascertain the object’s weight, whilst enclosing the object with one or both hands was used to tell what the overall shape of the object might be. The use of the term ‘exploratory procedure’ suggests that the way we obtain haptic information has a lot in common with active perception and the ideas of Gibson that were discussed previously; in fact it was Gibson who first coined the phrase ‘haptic information’ (Gibson, 1966). If we just sat still and did not attempt to explore our environment using our hands, we would not gain very much new

61

Key Term Haptic perception Tactile (touch) and kinaesthetic (awareness of position and movement of joints and muscles) perception.

Key Term Active perception Perception as a function of interaction with the world.

62

Chapter 2 | Perception information at all. Instead, on most occasions we have to interact with the environment actively to generate haptic information that will be of use. It is also the case that we can think about our sense of touch (and kinesthesis) in terms of ‘bottom-up’ and ‘top-down’ processing. A lot of haptic information is likely to be processed in a very bottom-up manner: for example the information about the texture and resistance of my keyboard keys and the relative position of my fingers can be said to flow from my senses upward through the perceptual system. However, haptic information can also have a top-down element and one excellent example of this is the parlour game where blindfolded people are asked to guess what object has been placed in their hand. Although this task involves considerable bottom-up processing, it is likely that the person would use their prior knowledge regarding the size, shape, weight and texture of objects to form and test hypotheses as to what the object might be.

USING ILLUSIONS TO EXPLORE HAPTIC INFORMATION One of the key approaches to distinguishing between top-down and bottom-up processing is based on illusions. You may remember that the Müller-Lyer illusion provides evidence of top-down processing, as we use existing knowledge to interpret the lines and mistakenly decide that one is longer than the other. Interestingly, there is evidence that the Müller-Lyer illusion works for haptic as well as visual information. Heller et al. (2002) produced a version of the illusion in which the lines were ‘raised’ (in a similar fashion to Braille) to allow them to be felt and participants estimated the size of the key lines using a sliding ruler. Blindfolded-sighted, late-blind, congenitally blind, and low-vision participants completed the task and all were influenced by the illusion, i.e. they estimated the ‘wings-in’ line to be shorter than the ‘wings-out’ line. Not only does this experiment demonstrate that the Müller-Lyer illusion is not reliant on either visual imagery or experience, it also suggests that there is an element of top-down processing with haptic information, just as there is with visual information. Previously, the concept was introduced that haptic information was generated by combining information from our sense of touch with proprioception and kinesthesis, but as we reach to feel or pick up an object we also need to take account of the information picked up by other senses, most notably vision. That both vision and haptic information are used to explore or pick up an object with our hands is obvious, otherwise it would be just as easy to pick something up with our eyes closed as it would with them open. As well as demonstrating visual top-down processing, illusion studies can also show the extent to which visual and haptic information is integrated. Gallace and Spence (2005) constructed a task that involved participants looking at the Müller-Lyer illusion whilst at the same time attempting to tell which of two sticks hidden from view was the longer. The sticks were placed directly behind the Müller-Lyer illusion (see

2.4 Haptic perception

63

Figure 2.26 A (CGI) recreation of the task from the Gallace and Spence (2005) study in which a participant feels the length of two unseen sticks placed behind the Muller-Lyer illusion. Source: Adapted from Gallace and Spence (2005).

Figure 2.26), which was presented in a horizontal ‘< > ‘jumped’, ‘hand’ > ‘handed’, ‘hum’ > ‘hummed’. These are termed regular past-tense inflections, as the bound morpheme is added in an identical way for each verb morpheme (although their pronunciation can differ – try saying ‘jumped’, ‘handed’ and ‘hummed’ and you will note that the ‘-ed’ ending sounds different in each, coming out more like a ‘-t’ in ‘jumpt’, ‘-ed’ in ‘hand-ed’ and a ‘-d’ in ‘hummd’). There are a great many of these regular past-tense verbs, at least 10,000 in English. These regular inflections can be contrasted with past-tense verbs like ‘eat’ > ‘ate’, ‘have’ > ‘had’, ‘run’ > ‘ran’. For these

10.6 Explaining lexical access in language comprehension irregular verbs, the past-tense verbs cannot be simply predicted from the present-tense form, and they can be phonetically very dissimilar (e.g. ‘tell’ > ‘told’). There are many fewer irregular verbs, around 106 in English, and they typically are very high in frequency – that is, they are very commonly used verbs. There is considerable debate about the ways that these two forms of past-tense verbs are represented cognitively: do we encode and represent this information in a symbolic, rule-like fashion, or can a distributed cognition account adequately explain the existence and processing of these regular and irregular forms? These two positions have very different theoretical imports: the symbolic processing model accounting for an explicit syntax in the construction of past-tense verbs. Following on from the conceptual position of Chomsky, Pinker (1999) proposed that regular verbs were formed by rule-based processes, while irregular verbs are formed by lexical mechanisms, which bear more in common with semantic processing than with rule-based mechanisms. In contrast, as will be established in Chapter 12 on connectionism, a parallel-processing account of regular and irregular verbs does not require any explicit rules or syntax. From the symbolic representation position, the regular verbs have been described as a ‘paradigm example’ of a rule-based system: a very simple bound morpheme is added to a verb to make the pasttense form. Although the phonetic realisation of the ‘-ed’ ending can differ, this is still predictable from the form of the original verb morpheme. Pinker identified three predictions of this approach which support this two-stage process: first, that the acquisition of the pasttense regularisation rule should be very rapid, even instant; second, that the application of the rule be uniform in its application (e.g. not be influenced by semantic information) and third, that the rulebased regular system is distinct from the lexically mediated irregular system. There is a lot of evidence to support this position. First, many children use past tenses (both regular and irregular) correctly at first, and then go through a stage where they over regularise, producing statements like ‘we goed to the zoo’ or ‘I eated that’. Simple association learning is held to be unable to account for this, as the children will not have (generally) been exposed to these incorrect versions, and they had previously been producing the correct version. Pinker has identified this as a sudden ‘eureka’ moment, where children come up with the rule which they then start to apply both accurately and inaccurately. The uniformity of the regular rules is seen, according to the Pinker approach, by the use of regular inflections as a default construction of the past tense – if no irregular construction is formed (by the lexical mechanism) a regular form will be produced. There has remained considerable debate about the extent to which a symbolic, rule-based system is necessary to model the past-tense inflections of English. For example, an early parallel distributed processing

321

322

Chapter 10 | Language model by Rumelhart and McClelland (1986) with modifiable connections between verb root representations and the phonological form of the past-tense verbs, was not only able to learn both regular and irregular past-tense verbs, but also showed the same pattern of early, correct application of regular and irregular inflections, followed by a period of over- regularisation. This demonstrated that apparently ‘rule-like’ behaviour can arise from a non-symbolic system which has no rules built into it. There are some other specific criticisms of some of the central assumptions of the Pinker model. The suddenness with which children acquire the regular past-tense rule has been queried: since any one child’s profile of verb productions, both correct and incorrect, can be very noisy and infrequent, it is possible to identify both patterns of immediate rule gaining (e.g. an increase of regularisations from 0 to 100 per cent over three months), and of slow rule acquisition (22–44 per cent over 6 months) from the same child’s data. Notably, for example, the 100 per cent profile was based on eight observations (McClelland and Patterson 2002). It is certainly not the case that a clear and unambiguous onset of a rule use is seen in the data. There are also problems with the way that the regular rule is considered to apply in a uniform way, that is, that the application of this rule is not influenced by semantic or phonetic information. Thus both regular and irregular inflections of past-tense non-words are judged to be more acceptable if they are phontactically well formed and come from a higher ‘island of reliability’, which is similar to orthographic and phonological neighbourhood density, and forms a measure of how many real words are similar to the non-word. Thus, the use of the regular rule can be influenced by phonological properties – the application is not necessarily uniform. Likewise, if a non-word like ‘flink’ is produced in a context where is could be more semantically linked to ‘drink’ it will be more likely to be inflected as ‘flank’ than if it were semantically linked to ‘blink’. This is an indication that the regularisation rule is not insensitive to semantic properties. In English there is a tremendous dominance of regular verbs – 86 per cent of the most frequent 1000 verbs in English are regularly inflected (McClelland and Patterson 2002). However, it is not clear that regularisation – application of the regularity rule – is the default way of generating past tenses when no lexical irregular form is available. The Pinker argument requires that the default use of regular rules is not a consequence of their frequency, but because they reflect a truly linguistic mechanism. It is thus necessary to identify languages in which there are both regular and irregular inflections, but where the regular inflections are less common than the irregular. There are few of these, comprising the regular German past tense ‘-t’, the Arabic broken plural and the German ‘+s’ plural. It transpires that both the regular German past tense ‘-t’ and the Arabic broken plural are both in fact less frequent than has been claimed (McClelland and Patterson, 2002). Furthermore, the German plural ‘+s’, while less frequent, is not applied as the default inflection in language use. It may thus not be possible to make the claim that the rule-based mechanism is the

10.7 Sentence comprehension default mechanism, even when it is less frequent than the irregular, lexical mechanism. In contrast to the two-stage rule-based mechanism, McClelland and Patterson identify a connectionist model by Joanisse and Seidenberg (1999) as a likely, parallel distributed processing alternative. Unlike the original Rumelhart and McClelland (1986) model, this model of verb inflection has a route for semantic as well as phonetic influences on the learning of correct inflections. McClelland and Patterson make the point that a connectionist model, which can exploit any regularities in the input, can learn the quasiregularities which are found in the vast majority of irregularly inflected verbs (e.g. fall and fell). In other words, ‘irregular’ verbs are typically somewhat regular, and are part of a family of similarly declined verbs: indeed, in English only ‘be’ and ‘go’ are fully irregular and can neither be predicted, nor share commonalities with other verbs. It has been argued that quasiregularity may actually be the norm in linguistic systems, and a model of past-tense verbs which can learn about these statistical relationships between phonological forms and past-tense declensions will have strengths over models which do not (McClelland and Patterson, 2002).

10.7 SENTENCE COMPREHENSION We are continually confronted with ambiguity in language, though we read the sentence ‘Time flies like an arrow’ we are seldom aware that there are more than 100 legal syntactic interpretations (Altmann, 1998). However, we do consistently find certain grammatically correct sentences confusing, and will often find them to be ungrammatical. These may shed light on how we are dealing with ambiguity in sentences. Take for example: The car raced past the crowd crashed. The car driven past the crowd crashed. Although both sentences are grammatically correct, the first is often considered to be ungrammatical. The problem is that ‘raced’ is ambiguous – it can be processed either as the main verb of the sentence, or as a past participle – a past-tense passive form of a verb, used here to describe something about the car in the sentence. If ‘raced’ is processed as the main verb, then ‘the crowd crashed’ becomes hard to process and the sentence feels ungrammatical. In contrast, ‘driven’ can only be a past participle, not a part-tense version of a verb (which would be ‘drove’). This makes the second sentence considerably more acceptable. We also experience problems with sentences like this: I will read the paper that you submitted tomorrow. We tend to associate the word ‘tomorrow’ with the immediately previous phrase ‘that you submitted’. This immediately feels wrong as

323

324

Chapter 10 | Language there is a clash between the past-tense of ‘you submitted’ and the word ‘tomorrow’ (Altmann, 1998). For a long while, the explanation for this is that certain syntactic structures are more easily processed than others, and that certain syntactic processing principles can lead us consistently into confusion. Two particular syntactic preferences have been identified as important in this respect (Kimball, 1973; Frazier, 1979). The first principle is associated with a preference for a simple syntactic structure rather than a complex one. As the perception of ‘raced’ as a past participle requires a sub-clause in the sentence, this makes for a more complex syntactic structure than the perception of ‘raced’ as the main verb of the sentence. The second principle, as in the sentence ‘I will read the paper that you submitted tomorrow’ is called ‘late closure’ and refers to a tendency to associated incoming information with the most recent information acquired. These two principles mean that we will consistently misunderstand certain syntactic frameworks, where the construction is not simple and words associated with earlier noun phrases are found towards the end of a sentence. This perspective was very consonant with a psycholinguistic emphasis of the role of syntactic structure on human language processing, where a syntactic processor which is informationally encapsulated (i.e. not influenced by other kinds of information) works through the incoming sentence. However, a more recent view, strongly influenced by models of word recognition, has been put forward in opposition to this, which uses probability and context as ways of driving the interpretation of words in sentences (Altmann, 1998). In this model, as words are read, multiple meanings are activated, with the activation weighted by probability of that particular meaning. The context in which the sentence appears also affects the weighting of the activation of any one meaning. This means that word meaning that is normally high probability can become lower in activation because of the semantic context in which it appears (Altmann, 1998). According to this approach, a sentence like ‘The car raced past the crowd crashed’ is harder to understand because the verb ‘raced’ is ambiguous – it can be either transitive (someone is racing something) or intransitive (someone is racing). As we have seen, this verb can also form the main verb of the sentence, or form a past participle, where it is defining aspects of the meaning of one of the words in the sentence but is not the main phrase. These two properties of verbs interact: a past participle must be transitive (as something is being raced by someone), while a main verb can be either transitive or intransitive (Altmann, 1998). As Altmann points out, verbs vary a lot in these probabilities, with some verbs appearing as past participles very often (e.g. ‘enjoyed’) and some less often (e.g. ‘received’), and readers will use this information to interpret the meaning of the sentence. Readers will also use semantics to constrain the interpretation of words: In a sentence starting with ‘the chef fed’, readers will use the semantic knowledge that chefs are generally cooking for other people to interpret ‘fed’ as a main verb,

10.7 Sentence comprehension not a past participle. People will also use the plausibility of whether the subject of a sentence is animate or inanimate to interpret sentences. Take for example: The page ripped by the toddler was mended. The page that was ripped by the toddler was mended. The phrase ‘by the toddler’ takes longer to read in the first sentence than if the same phrase appears after ‘that’ in the second sentence (Trueswell, 1996). This has been interpreted to show that although inanimate objects rarely rip things, the readers are trying to process ‘ripped’ as the main verb of the sentence, in the absence of cues like ‘that’ which indicate sub-clauses to the sentence. This indicates that the main constraint on the processing of this sentence concerns the plausibility of ‘ripped’ being a main verb or a past participle (Altmann, 1998). People will also use a wider context to help understand a sentence, as in the following: Put the orange on the plate in the bag. People hearing the sentence will often assume that ‘put the orange on the plate’ is the start of the instruction, and have difficulty with ‘in the bag’. In an experiment testing whether this effect can be modulated, participants were played sentences with instructions in, and shown pictures like those in Figure 10.3. Experiments have shown that this kind of visual context leads people to interpret ‘on the plate’ as a description of which orange is being discussed, not as part of the action to perform upon the orange (Tanenhaus et al., 1995). Importantly, this kind of research is performed with data about eye movements being collected as people process the sentences, and these studies have shown that as soon as ‘on the plate’ is heard, the participants look at the picture of the orange on the plate. In terms of constraint satisfaction as a model of sentence processing, the influences of these different sources of variability in interpretation will vary depending on their probability. Thus the stronger one kind of cue is (e.g. the probability of certain argument structures, like main verbs occurring early in the sentence), the weaker the influence of other kinds of cues (e.g. the likelihood of pages ripping things). In normal speech perception, it must be stressed that prosodic and intonational cues are another highly important way that talkers cue listeners into their intended meaning, with the result that these kinds of confusions are harder to Figure 10.3 Testing the effect of visual context on establish in informal speech. Indeed, in interpretation of a sentence.

325

326

Chapter 10 | Language normal reading, the job of punctuation is to help readers deal with this kind of complex structure (often by explicitly implying aspects of speech intonation and timing). This does not take away the importance of these constraint-based models of sentence comprehension but it does mean that language has a structural context (prosodic or derived from punctuation) which also facilitates comprehension.

10.8 LANGUAGE PRODUCTION Speech production – deciding what we want to say, and articulating this accurately and fluently – is a behaviour which we take very much for granted, and which we typically do extremely well – it has been estimated that any one talker uses a production vocabulary of around 20,000 words, but that we make mistakes of word selection in only around every one in a million words produced. The processes involved in turning thoughts into spoken words are called lexicalisation, and two main stages have been hypothesised (Levelt, 1989, 1992). The first stage comprises a link between conceptual thoughts and word forms which include semantic and syntactic information, but not phonological detail. This is called the ‘lemma’ and the processes of identifying and choosing the correct word is called lemma selection. In the second stage, the lemma makes contact with the phonetic representation of the word, called the lexeme, and the specifying of this form is called lexeme selection. Much of the evidence for this two-stage form of word selection in speech production comes from a frustrating state that many people have experienced, called tipof-the-tongue state. When in this condition, people have an absolute certainty that they know a word that they want to say, combined with a lack of sensation of how they should say it. In this state, people can often access a lot of information about a word, such as what it means and aspects of its syntax, and this has been ascribed to being able to access lemma information, without being able to make contact with the lexeme detail (Harley, 2001). There is also experimental evidence for these stages from studies of priming, for example, participants name pictures more quickly if they had previously named or defined the word, but not if they had produced a homophone which sounds the same but has a different meaning. This suggests that priming at the lemma level (semantic and syntax) can operate separately from lexeme (phonological) priming. Historically, another influence on our understanding of speech production processes comes from studies of speech errors, or ‘slips of the tongue’. Fromkin (1973) said these errors ‘provide a window into linguistic processes’ (pp. 43–44), although it has also been pointed out that these errors rely on accurate acoustic and phonetic decoding by the listener, which comprise a complex set of psychological processes (Boucher, 1994). There are consistencies in the kinds of errors speakers make, where the errors occur at the level of phonemes, morphemes or words, rather

10.8 Language production than random noisy patterns of errors. This gives weight to the suggestion that they result from specific kinds of errors in the speech production system (Fromkin, 1971, 1973; Garrett, 1975; Dell, 1986; Harley, 2001). Garrett developed a model of speech production based on a set of speech errors which he considered to be particularly informative: r
Word substitutions – these affect content words, not (typically) form words, such as ‘man’ for ‘woman’ or ‘day’ for ‘night’. r
Word exchanges in which words from the same category swap positions with each other, such that nouns swap with nouns, verbs with verbs, etc. r
Sound exchange errors such as classic spoonerisms such as ‘wastey term’ for ‘tasty worm’, where the onsets of words swap positions with each other, commonly over words which are next to each other. r
Morpheme exchange – this is where word endings (morphological inflections) move to other points in the sentence, such as ‘Have you seen Hector Easter’s egg?’ for ‘Have you seen Hector’s Easter egg?’. Morpheme exchange errors can also include ‘stranding’ errors such as “Have you seen Easter’s Hector egg?”. In Garrett’s model of speech production there are several, independent levels involved in speech production: 1. the message level, which represents the concepts and thoughts that the speaker wants to express; 2. the functional level, at which these concepts are expressed as semantic lexical representations, and thematic aspects of the sentence (the subject and object, for example) are also represented – i.e. the roles that these semantic items will take in the sentence; 3. the positional level, at which the semantic-lexical representations are implemented as phonological items, with a syntactic structure; 4. the phonetic level, at which the phonological and syntactic representations are realised as detailed phonetic sequences, precisely articulating the word forms and inflections specific by the positional level; 5. the articulation level, which form control of the vocal apparatus to express the In Garrett’s model, the semantic information about content words is specified at the functional level, while function words and bound morphemes (such as ‘-ing’ endings) are added to the sentence structure at the positional level, where they are associated with their phonetic forms: in contrast, the phonological forms of the content words needs to be generated within the sentence at the positional level. This kind of constraint in the model allows for word substitution errors, which are generated at the functional level (or the lexical level in Levelt’s model), and which infrequently affect form words. Likewise, sound exchange errors arise when content words are being

327

328

Chapter 10 | Language phonologically constructed at the positional level, and again, affect form words much less (as they are phonologically prespecified at this level). Stranding errors occur when the content words are being positioned in the sentence, which occurs before syntactic structure and inflections are added to the sentence. This is a serial model of speech production: speech production is a result of a series of independent output stages in which there are distinct computational processes specified in a serial, noninteracting fashion; this is also true of the Levelt model. There are other approaches to modelling speech production which proceed along more parallel lines, and which are typically modelled within the connectionist, interactive framework – for example, the speech production model of Gary Dell (Dell, 1986; Dell and O’Seaghdha, 1991; Dell et al., 1997). In this model, a spoken sentence is represented as a sentence frame, and is planned simultaneously across semantic, syntactic, morphological and phonological levels, with spreading activation permitting different levels to affect each other. This allows speech errors to be ‘mixed’: as Dell has pointed out, many speech errors (such as ‘The wind is strowing strongly’) represent several different kinds of errors. Functionally the Dell model works via different points in the sentence frame activating items in a lexicon – for example when a verb is specified, there will be activation across interconnected nodes for concepts, words, morphemes and phonemes. When a node is activated, there is a spread of activation across all the nodes connected to it. Thus if the node for the verb ‘run’ is activated, there will also be activation for the verb ‘walk’. Selection is based on the node with the highest activation, and after a node has been selected its activation is reset to zero (to prevent the same word from be continuously produced). In this way, word substitution errors occur when the wrong word becomes more highly activated than the correct target word. The model contains categorical rules which act as constraints on the types of items which are activated at each level in the model, and these rules place limits on the kinds of errors that can be made – nouns swapping places with nouns, for example. In contrast, exchange errors occur as a result of the increases in activation, which means that a lexical element (a phoneme, or a word) can appear earlier in a sentence than was intended, if its activation unexpectedly increased: as the activation is immediately set to zero once an item has been selected, another highly activated item is likely to take its place in the intended part of the sentence frame. As in other areas of cognitive psychology, there has been a lively debate about the extent to which speech production is well modelled by interactive connectionist models, or by more rulebased, serial, symbolic models. The two-stage model of Levelt was developed into a more complex six-stage model of spoken word production (Levelt, 1989; Bock and Levelt, 1994; Levelt et al., 1999 called WEAVER++ (Word-form Encoding by Activation and VERification). The stages are:

10.8 Language production 1. 2. 3. 4. 5. 6.

conceptual preparation; lexical selection (the stage at which the abstract lemma is selected); morphological encoding; phonological encoding; phonetic encoding; articulation.

Like Dell’s model, WEAVER++ is a spreading activation model, but unlike Dell’s model, activation is fed forward in one direction only, from concepts to articulation: furthermore, the WEAVER++ model is truly serial, as each stage is completed before the next stage is started. In an experimental attempt to generate speech errors, Levelt et al. (1991) required participants to name pictures while also listening to words, and pressing a button when they recognised a word. The relationships between the seen objects and heard words varied – there were semantic relationships, phonological relationships and unrelated pairs, and some had a ‘mediated’ relationship to the picture, that is, linked through a semantic and phonological connection. If the picture was a dog, a mediated relationship word could be ‘cot’, which is phonologically similar to ‘cat’, which in turn has a semantic relationship with ‘dog’. The study was specifically designed to test the hypothesis, inferred from Dell’s model, that a model of speech production in which different levels can interact would predict a facilitation of naming ‘dog’ when ‘cot’ is heard (Levelt et al., 1991). Experimentally, this predicted facilitation was not found: there was no phonological activation of semantically related items. In contrast, the results supported a sequential model. Specifically, there was priming of lexical decisions to the heard word from semantically related words only at very short intervals (around 70 ms), while priming of lexical decisions from phonologically related words was only significant at longer intervals (around 600 ms). These results were taken to support a sequential, stagebased implementation of word naming. There is evidence in favour of the Dell model, however: Morsella and Miozzo (2002) asked participants to name pictures in the presence of other (distractor) pictures: there was facilitation of picture naming when there was a phonological relationship between the target and distractor pictures. This was taken to show a beneficial effect of phonological information at an earlier stage in word selection and production than would be predicted by a feed-forward, sequential model like Levelt’s. Speech production has been somewhat less closely studied than other aspects of language in cognitive psychology (especially when compared with the detailed investigations of speech production seen in the aphasia literature as will be seen in Chapter 11); however, that profile is changing rapidly as a range of experimental techniques are becoming available to researchers (Griffin and Crew, 2012).

329

330

Chapter 10 | Language

10.9 DISCOURSE LEVEL Human language is not just an extraordinarily complex system for representing and processing information; it is also the dominant system within which we communicate with each other. Discourse is the term that refers to the higher-order aspects of language use, both in terms of how connected ideas are expressed (e.g. over the course of sentences) and in conversation, which is the shared use of language in interactions (be those interactions spoken, signed or written). Conversation is an extremely interesting and complex use of language for several different reasons. It is the context in which we acquire spoken language – all of us learn to speak (or sign) in interactions with others. Conversation also represents an extremely good example of well-coordinated behaviour; a verbal behaviour which relies on very high-order use on intentions and thought, and our main social tool for interactions.

COORDINATING CONVERSATIONS When we have conversations with people, certain universal rules are followed. These have been summarised by Sacks et al. (1974) as: 1. 2. 3. 4. 5.

Speaker change occurs. One person speaks at a time. Simultaneous speech is common but brief. Transitions with no gap and no overlap are common. Turn order is not fixed, nor is turn size, duration of a turn or content. 6. Number of talkers can vary. 7. Talk can be continuous or discontinuous. Speakers in a conversation are generally excellent at following these rules, and if you’ve ever had the unpleasant experience of talking to someone who won’t let you take your turn, you’ll be struck how infrequently this happens. The principles exist probably because they form a natural framework in which relatively unconstrained conversation can be easily managed. It has been observed that the maximum limit on conversational partners is around four to five people – if a social group gets larger than this, separate sub-groups of conversational partners will emerge (Dunbar et al., 1995). The exact reason for this has yet to be determined; however, it may well be a result of following the principles of Sacks et al. with larger numbers of people: that is, it may be relatively simple for two to four people to negotiate the acceptable boundaries of conversation (e.g. managing who speaks next) but much harder for six to seven people. The management of turn-taking in conversation is very important: even in phone conversations, complete strangers, who cannot see each other, manage to take turns in the conversation very smoothly. The vast majority of intervals between talker turns in conversation fall within a range of 150 ms (e.g. De Ruiter et al., 2006). This speed is

10.9 Discourse level far faster than one would expect to see if turns were entirely reactive, that is, the preparation for a turn were to start when the prior talker has finished their turn, which would be associated with far longer reaction times. Instead it has been suggested that talkers in a conversation start to entrain their behaviour with each other, speaking at the same rates as each other, and that talkers time their turns based on the speech rhythm and prosody of the other talkers during their turns (Wilson and Wilson, 2005). Indeed, conversation has been described as an incredibly detailed exercise in coordinating our verbal behaviour with that other our co-talkers: when we talk to other people, we start to coordinate our breathing and speech rate with each other. We also start to coordinate the language that we use: when we talk to each other, we will start to use the same words and the same grammatical constructions (Garrod and Pickering, 2004).

MEANING AND INTENTION IN CONVERSATION One of the intriguing facts about conversational speech is that we almost never say exactly what we mean: if my partner comes into the room and says ‘have you seen my phone’ he is hugely unlikely to be pleased if I respond ‘yes, you had it when you rang your mother this morning’. On the face of it, his question was about my having visual experience of his phone but in the context of his uttering it, it is of course an indication to me that (a) he is looking for his phone and (b) he wants to know if I know where his phone is. For me to understand his question accurately, I need to decode not simply the words that he says but his underlying intentions. This is a pragmatic use of language and it means going beyond the words someone says. One of the first people to explore this topic was Grice (1975), who established that when a someone talks, it important to decode their intentions in addition to their words. Grice described talkers as implying much if the information in their statements: if I say that ‘I am not going to the party, I’m feeling tired’, one can interpret my meaning by assuming the reason why I am not going to the party is because I am feeling tired. Grice identified differences of implied meaning – which he termed implicatures – which ways if describing the meaning implied in speech acts. He identified different kinds of implicatures: 1. Conventional implicatures – these arise through semantic representations of the meanings of particular ‘turns of phrase’ which are used in conversational speech. Thus someone may use the phrase ‘I have to say …’ at the start of a sentence and not be understood to mean that they are being forced to say anything. 2. Conversational implicatures – these arise from the concept that there is implied meaning in how sentences are constructed in speech; if a talker says, ‘I would take fish pie to the party but I think Jane is allergic’, the use of ‘but’ is drawing a contrast between the two statements. This kind of meaning is operating at a pragmatic level. 3. Cooperative principle – this principle entails that you should ‘Make your conversational contribution such as is required, at the stage

331

332

Chapter 10 | Language of the conversation at which it occurs, by the accepted purpose of direction of the talk exchange in which you find yourself.’ This principle leads to four maxims (Grice, 1975): the maxim of quantity – say what is informative for the discussion but no more (and no less); the maxim of quality – don’t say what is untrue (or what you consider to be untrue); the maxim of relation – which means, in short, that what you say should be relevant, or germane, to what is being discussed; the maxim of manner – try not to be ambiguous or hard to understand. In Grice’s theory, it is the operative use of these maxims that makes the conversational implicatures comprehensible to talkers in a conversation. Grice’s great insight was that in conversation, as we hardly ever specify exactly what we mean by the words we say, the important job for a listener is to understand a talker’s intentions. In conversations, the speech acts produced by a talker set up expectations in a listener that they infer on the basis of the implicatures in order to derive the meaning of what is being said: his perspective therefore is a highly active, inferential model of communication (as opposed to a more passive decoding strategy). This aspect of Grice’s work was developed by Sperber and Wilson (1985) who picked up on this active inferential model to explore the concept of relevance in communication. Essentially, Wilson and Sperber questioned the need for the maxims, principles and implicatures which Grice specified, and posited that the expectation of relevance was sufficient for the listener to start interpreting the utterances. Relevance, in this context, refers to a property of utterances, but also as a property of any piece of verbal information, from a thought to any observable phenomena. In this framework, relevance is considered to mean that uttrerances are assumed to be relevant, to be meaningful, to have a sense that we will be able to follow. Relevance is thus a property not of linguistic mechanisms that are recruited to understand speech, but of human cognition: we can understand spoken language because the quest for understanding, and the corresponding belief that information is meaningful, is an omnipresent property of human thought, and the ways that we engage with the world. In this light, I can understand what my partner means when he asks ‘Have you seen my phone?’ because I can also understand what an ominous clunk means when I hear my son drop his dad’s phone onto a flagged stone floor. Indeed, in more recent implementations of their theory, Wilson and Sperber have been extending relevance to properties of human cognition (Wilson and Sperber, 2002).

SOCIAL CONVERSATIONS In psychology textbooks we tend to give examples of conversations which include lots of people marching around looking for lost

10.9 Discourse level phones and uttering excuses not to go to parties. However, human language is not only the main way that we share information with each other, it is also the main way that we make and maintain our social connections, and when we talk to each other in this way, our conversation is rarely composed of demands for information or statements of intent. Instead, the main thing we do when we talk to our friends is to discuss other people (Dunbar et al., 1997). As we are social primates, it is not perhaps too surprising that the most interesting things we have to talk about are other people. It has even been suggested that human language has replaced social grooming for humans: for non-human primates, an individual’s position in the social hierarchy is made manifest by whom they groom and whom they allow to groom them, and social grooming is a very important aspect of primate life, for this reason. In humans, social language has been hypothesised as the main way that we show with whom we have our important social links. In line with this, humans have exploited other forms of communication than face-to-face conversations since we have been able to write to one another, and over the centuries this has exploded with communication on phones and text, from SMS and email to online social media like Facebook and Twitter. Notably, however, we enjoy face-to-face conversation most of all, even if that face-to-face conversation takes place on a computer: studies have shown that we rate ourselves as happier, say that we have laughed more, and keep the conversation going for longer for face-to-face conversations (both in the presence of the other talkers and online) than phone conversations, text messaging or email interactions (Vlahovic et al., 2012). Indeed, the precise linguistic aspects of our spoken language are influenced by social context: if my partner indirectly asks if I’ve seen his phone, and I respond (with very reduced articulation) ‘dunno’, this might be acceptable in a way that it would not be if he was asking me directly if I let our son drop his phone on the stone floor (when a more fully fledged speech act would be required in response) (Hawkins, 2003). When we speak with people we like, all the processes of alignment that we saw in the earlier section are enhanced, such that we will use the same words and syntax as someone else, the more we like them. We not only learnt to speak in conversations, we have those conversations with the people close to us, emotionally and physically, and this may lead to a lifelong enjoyment in talking to the people we want to be with, which in turn influences our own speech.

NOTE 1.

In the dedication to The Modularity of Mind, Fodor writes: ‘[…] Merrill Garrett made what seems to me the deepest remark that I have yet heard about the psychological mechanisms that mediate the perception of speech. “What you have to remember about parsing,” Merrill said, “is that basically it’s a reflex”.’

333

334

Chapter 10 | Language

SUMMARY t
Speech is an extremely complex sound and way of expressing language: other ways include written language and sign language. t
Languages have structure at a number of different levels from phonetic, morphological, lexical, semantic and syntactic, through to pragmatic meaning. t
Linguistics aims to understand language as a complex system, and psychologists have been interested in identifying how this can inform human language use. There may be some important differences in these approaches, not least because linguists have historically tended to underplay a role for learning. t
Several different factors have been implicated in how we recognise written and spoken words, and database approaches have opened up the possibility of analyses these influences in a complex multifactorial way. t
Sentence comprehension has been strongly influenced by models from psycholinguistics; however, approaches influenced by research into word recognition have shown important roles for biasing effects of probabilities and contexts in sentence comprehension. t
In models of language processing, there is a tension between approaches which favour symbolic, rule-based processing models, and approaches which favour a more interactive, connectionist approach. Past-tense verbs in English have been identified as key in testing claims in this debate. t
Speech production involves a number of different kinds of representation and the extent to which these may or may not interact when speaking is debated. t
Using speech in conversation is highly complex, and social and affiliative behaviours start to interact with cognitive and linguistic processes at this level.

FURTHER READING t
Berko-Gleason, J. and Ratner, N. (1997). Psycholinguistics, 2nd edn. Orlando, FA: Harcourt Brace College Publishers. An excellent introductory text, very well presented. t
Carroll, D. W. (2003). Psychology of Language, 3rd edn. Belmont, CA: Brooks/Cole. This is a good introductory textbook covering a wide range of topics in an accessible way. t
Clark, H. H. (1996). Using Language. New York: Cambridge University Press. A stimulating account of the way people cooperate together in speaking and listening, participating in the joint enterprise of using language for conversational interaction.

10.9 Discourse level

t
Harley, T. A. (2001). The Psychology of Language: From Data to Theory, 2nd edn. Hove: Psychology Press. This is a very comprehensive textbook on the psychology of language, more advanced than the Carroll or Whitney texts and with more coverage of UKbased research. Highly recommended. t
Pinker, S. (1994). The Language Instinct: The New Science of Language and Mind. Harmondsworth: Penguin. A fascinating and exceptionally well-written exploration of the nature of language and its role in our mental makeup. A really good read. t
Whitney, P. (1997). The Psychology of Language. Boston, MA: Houghton Mifflin. A good introductory text.

335

Chapter 11

Contents 11.1 Introduction

337

11.2 Models of aphasia

339

11.3 Detailed symptoms of aphasic profiles

346

11.4 Psychological and psycholinguistic aspects of aphasia

351

11.5 Functional imaging of human language processing

353

11.6 Reading

358

11.7 Developmental disorders of language

365

Summary

368

Further reading

369

Disorders of language Sophie Scott 11.1 INTRODUCTION How is language represented in the human brain, and how can linguistic functions be impaired? This chapter will outline the historical background of these studies and also address more recent developments in the ways that these linguistic processes can be investigated. There are two different general ways in which human brain function can be disrupted, which are acquired damage and developmental disorders. In acquired damage, a healthy brain is lesioned, for example, via a stroke (where the blood supply to the brain is disrupted), disease (e.g. encephalitis), a tumour, trauma (e.g. a penetrating object), or a progressive disease such as Pick’s disease. These causes of brain damage are all different in terms of what leads to them, what kinds of damage they cause and what kinds of recovery are possible, but all lead to a non-transient disruption in brain function. The second route is via a developmental disorder, such as autism, or specific language impairment, where the brain is affected either during its development in utero (e.g. due to genetic factors) or during birth. The emphasis here is less on how the brain is damaged, and more on how a child’s behaviour and brain function is affected over the course of development. Much of the history of language disorders has been based on acquired disorders, but there are also several developmental disorders which affect language, and I will address these towards the end of this chapter. The first cognitive functions to be localised in the human brain were associated with language. In the 1860s, following influential theories about whether or not the human brain was organised with different specific functions associated with different anatomical locations, there was a developing consensus that areas in the left frontal cortex might be critical for the production of speech (see Levelt, 2012). A neurologist called Paul Broca was specifically interested in such cases, when he was introduced to a patient known as ‘Tan’, an adult Frenchman with an expressive disorder of spoken language (i.e. acquired brain damage). Over the previous 21 years, Tan’s speech had worsened, although his general mental abilities remained intact. By the time he came to

11 Key Term

Lesion Refers to tissue damage – in the brain this can be a result of a stroke, a tumour, an infectious disease, the effects of a toxin, a direct injury or a progressive disease (a dementia). Stroke Refers to brain damage which occurs as a result of cardiovascular issues. The brain is an energy-intensive organ, using around 20 per cent of the available oxygen circulating in the blood supply. Disruption to blood supply causes brain damage to occur very quickly. The damage can occur due to a blockage in a blood vessel (an ischaemic stroke) or due to a blood vessel rupturing (haemorragic stroke). Strokes are associated with sudden onsets of symptoms of brain damage, and the symptoms can reduce in severity as time passes.

338

Chapter 11 | Disorders of language

Key Term Gyrus The surface of the brain is formed by the cerebral cortex, and this has its surface area greatly increased by being thrown into folds. A gyrus is the outer surface of one of these folds, and a sulcus is formed when in the depths of a fold. If the fold in the cortex is very deep it is called a fissure, like the lateral fissure which separates the temporal lobe from the frontal lobe. Aphasia An acquired language disorder, which primarily affects the comprehension of spoken language (a receptive aphasia), or the production of spoken language (expressive aphasia). In global aphasia, both speech production and perception are compromised. Neologisms Non-words which can be used by some neuropsychological patients in place of real words. The patients frequently do not know that they are not using real words. More widely, neologisms are used to refer to new words which are making their way into wider, more commonplace language use.

Broca’s attention, Tan could no longer produce any intelligible speech, uttering only ‘tan’ and some swearwords (Broca, 1861b). Broca was keen to know which brain areas might be damaged in Tan. However, relating behavioural changes to brain damage was not easy at the time; until the late twentieth century, when techniques such as CT scans and MRI scans became available, neurologists were limited to postmortem analyses to investigate the human brain. Tan died shortly after meeting Broca, and a post-mortem was conducted at which Tan was found to have brain damage (typically called a brain lesion), caused by a tumour associated with syphilis in the front half of the left side of his brain. Specifically, the lesion lay in the posterior (back) third of the left inferior frontal gyrus (Figure 11.1). Over the next century, this brain area became known as Broca’s area, and associated with a disorder of speech production called Broca’s aphasia. Broca’s aphasia is characterised by halting, non-fluent speech, with many grammatical errors. Broca’s aphasia was considered to result from a loss of motor memories for speech, and nowadays it is often associated with difficulties in selecting and planning the control of speech acts. Shortly after Broca’s influential paper, Karl Wernicke (1881) described patients with disorders of speech comprehension, that is, people who developed difficulties understanding spoken language: this is typically described as a sensory, or receptive aphasia. Wernicke determined that patients with a sudden onset of speech comprehension difficulties had damage to the left superior temporal gyrus (Figure 11.2). A deficit in understanding spoken language after brain damage became known as Wernicke’s aphasia. Speech production can be intact in people with Wernicke’s aphasia. However, in some cases people’s speech can be disordered in content, such that their speech is difficult to understand; it can be made up of random words, a so-called ‘word salad’, or consist of made up words (known as neologisms).

Supplementary motor area

Primary motor cortex Central sulcus Primary somatosensory cortex

Pre-motor cortex Superior frontal gyrus

Posterior Anterior

Broca’s area

Inferior frontal gyrus

Figure 11.1 1861b).

Diagram of the brain showing the position of Broca’s area (Broca,

11.2 Models of aphasia

Supramarginal gyrus

Primary auditory cortex

Angular gyrus

Superior temporal gyrus Posterior Anterior

icke’s

Wern

area

Inferior temporal gyrus Superior temporal sulcus

Figure 11.2

Middle temporal gyrus

Diagram of the brain showing Wernicke’s area (Wernicke, 1881).

11.2 MODELS OF APHASIA THE WERNICKE–LICHTHEIM MODEL OF APHASIA AND ITS MODIFICATIONS Wernicke used his insights into the problems of patients who had difficulties in understanding spoken language, and the ways their problems differed from individuals with Broca’s aphasia, to develop a model of speech perception and production (Figure 11.3). In terms of cognitive processes, Wernicke realised that the two different profiles of the ways that language could be affected by brain damage indicated that there were some underlying differences in how these processes and representations must be implemented in the human brain. In terms of modern cognitive neuropsychology, the findings that speech perception and speech production can be differentially and separably affected by brain damage is evidence for a ‘double dissociation’ (Shallice, 1988); double dissociations became a central feature of cognitive neuropsychology and cognitive science over the twentieth century, especially with the rise of cognitive psychology in the second half of the century. From the outset, these diagrams were both very popular and controversial: Levelt (2012) has recently outlined exactly how popular diagrams (or cognitive models as we would now call them) were, and also how critical people were: Henry Head, for example, considered that researchers would twist the clinical cases they observed to try and fit their models (Head, 1926). However, from the outset these models had the power of being testable and of being used to generate hypotheses. In terms of predictions, Wernicke predicted conduction aphasia as a consequence of his model, if there were a disconnection of the phonetic lexicon from the speech motor planning centre (lesion of line C in Figure 11.3), resulting in a problem where patients can

339

340

Chapter 11 | Disorders of language

Speech − phonetic movement programs D

Phonological lexicon B

C

E

A Auditory analysis (STG) A

Motor systems (motor cortex) F

Figure 11.3 Wernicke’s (1881) model of speech perception and production.

Speech output

Speech input

understand speech, but make errors in repetition. Wernicke’s model was tested by Lichtheim, who identified a potential kind of speech problem which the model could not account for. In transcortical sensory aphasia, patients have problems understanding speech, and fluent speech output (though their speech production can be confused). Unlike Wernicke’s patients, however, these patients can repeat accurately. In Wernicke’s model, there is no route for speech comprehension to be compromised, but for repetition to be intact. Lichtheim proposed the addition of a semantic-conceptual module to the Wernicke model. This model (Lichtheim, 1885) has been described as the first cognitive model that identified different subsystems in an information processing framework (Figure 11.4). Lichtheim’s modified model identified an output, motor module (D), an input store of phonological lexical information (B) and a

Semanticconceptual area F E

G

Speech − phonetic movement programs D

C

Phonological lexicon B

A

Figure 11.4 Lichtheim’s (1885) model of speech perception and production.

Motor systems (motor cortex)

Auditory analysis (STG) A

Speech output

Speech input

11.2 Models of aphasia conceptual centre (F). Lesions which disconnect or damage elements of this model lead to different profiles of aphasic problems. For example, Broca’s aphasia would result from damage to D, and Wernicke’s aphasia from damage to B. Damage to the connection between B and D would lead to a problem in connecting from sounds to speech output, and indeed in conduction aphasia, as predicted by Wernicke, affected individuals can produce speech, and can understand speech, but cannot repeat heard words. Further disruptions to speech production/perception following brain damage within this model of aphasia are classified in the Boston Aphasia Classification System (Goodglass and Kaplan, 1972).

THE BOSTON APHASIA CLASSIFICATION SYSTEM The Lichtheim model of language (and the associated predicted patterns of language breakdown) led to the Boston Aphasia Classification System, often called the classical, or neoclassical classification system of aphasia. These aphasic syndromes are categorised by their symptoms, and by the ways that they are considered to be indicative of different kinds of damage to the Lichtheim model of language. These aphasic syndromes can be considered to be the first application of the study of disordered function to test predictions of a cognitive model. Note that some of these aphasias are considered to be caused by damage to particular brain areas which underpin certain functions (e.g. Broca’s aphasia), and others are considered to result from damage to the pathways connecting different brain areas which are important in language – these are considered to be ‘disconnection’ syndromes. Thus, this approach distinguishes between damage to function and damage to connections between brain areas, which may mean that functioning brain areas can no longer contribute to a language task, because they have been disconnected by the damage. The Boston system is as follows: 1. Broca’s aphasia. Speech production is laborious and grammar can be incorrect. This is caused by a lesion involving the expressive speech centre (D). 2. Wernicke’s aphasia. Speech comprehension is impaired: patients find it hard to understand what is said to them. This is caused by a lesion of the audio-verbal centre, also referred to as the phonological lexicon (B). 3. Conduction aphasia. Patients can understand speech, and produce speech accurately, but they have specific difficulties with the repetition of heard words. This is caused by a lesion of the pathways connecting the audio-verbal and expressive speech areas (line C). 4. Global aphasia. Patients can neither understand or produce speech. This profile is produced by an extensive lesion involving both the audio-verbal centre (B) and the expressive speech centre (D). 5. Transcortical motor aphasia. Similar in symptoms to Broca’s aphasia, but the patient’s repetition skills are intact. The disorder is

341

Key Term Boston Aphasia Classification System A systematic classification of aphasic profiles which can be used to identify aphasia and to predict what profiles of damage a patients might be expected to show when assessing their damage. The Boston Classification System builds on the models of aphasia which were developed by Broca, Wernicke and Lichtheim. Implicit in this approach is the concept that language can be localised in the human brain, and that different profiles of language deficits are related to distinctly different patterns of brain damage.

342

Chapter 11 | Disorders of language associated with disruption of the pathways (shown in Figure 11.4 as line G) connecting the concept area (F) to the expressive speech area (D). 6. Transcortical sensory aphasia is similar to Wernicke’s, or receptive aphasia, except that repetition is preserved. Indeed, patients can show echolalia, where there is an obligatory repetition of heard words. This is a result of lesions of the pathways (shown in Figure 11.4 as line E) connecting the audio-verbal centre (B) to the concept centre (F). 7. Isolation aphasia, also known as mixed transcortical aphasia, is a disorder in which the patient cannot understand heard speech, and cannot produce speech, but can still repeat words. This disorder is caused by lesions, which disconnect the concept centre from the audio-verbal centre and the expressive speech centre (in Figure 11.4, these are disconnections of line E between B and F, and line G, between F and D). 8. Anomic aphasia is a disorder associated with a problem in naming objects, across modalities (e.g. patient cannot name a cow by seeing a picture of a cow, or hearing ‘moo’). Anomic aphasia can be caused either by a lesion involving the pathways which connect the concept centre to the expressive speech centre (line G in Figure 11.4), or if comprehension is also disrupted, a lesion of the concept centre itself (F). The problem with the definition of anomic aphasia, as Lichtheim himself noted, was that anomic aphasia and transcortical motor aphasia are caused by very similar damage in the Wernicke–Lichtheim model, but are clinically quite distinct (Heilman, 2006). There are several other issues with the Wernicke–Lichtheim model of aphasia – for example, as Sigmund Freud pointed out, there is no account in this model of why a patient with Wernicke’s aphasia might make (and fail to notice, let alone correct) frequent errors in their speech output, as they commonly do (Butterworth, 1993). A slightly different model was developed by Kussmaul (1877) who hypothesised connections from the semantic-conceptual area back to the phonological input lexicon: evidence from Feinberg et al. (1986) showed that people with conduction aphasia were able to tell whether or not pictures of words were pronounced the same way, even if they could not say those words aloud. This was evidence in support of Kussmaul’s claim. Lichtheim had also described a patient who could repeat words, but who had great difficulty in speech comprehension: the patient also produced errors when speaking (e.g. using the wrong words) and had problems naming. This profile of problems was hard to account for in the Wernicke–Lichtheim model, since a disconnection of the acousticphonetic processing field from the conceptual system would not produce these deficits (Heilman, 2006). If there are reciprocal connections between the acoustic-phonetic input lexicon and the semantic-conceptual system, then a disruption of these will produce the profile that Lichtheim had described. Figure 11.5 shows Kussmaul’s adaptations to the Wernicke–Lichtheim model. In this model there is no direct link

11.2 Models of aphasia

343

Semanticconceptual area F G

Speech − phonetic movement programs D

E

C

Phonological lexicon B

A

Motor systems (motor cortex)

Speech output

Auditory analysis (STG) A

Speech input

between the semantic-onceptual system and speech output planning in Broca’s area. Further support for the reciprocal connections between the semantic-conceptual system and the phonetic analysis/phonological lexicon came when a patient was discovered who had transcortical sensory aphasia – that is, impaired speech comprehension but intact repetition with intact naming and clear speech production (Heilman et al., 1981). The patient was unable to access semantic representations from phonological representations, but could access their phonological representations via intact processing from their semantic-conceptual module. The Wernicke–Lichtheim model had a link from semantic-conceptual representations to speech output systems to provide a system for the production of normal, spontaneous speech. This enables the model to explain transcortical motor aphasia, where patients can understand speech, but have great difficulties in production: unlike Broca’s aphasia, the patients can repeat words accurately. If the patients have a suspected deficit in activating semantic-conceptual models of what they want to say, this profile of aphasia is sometimes called adynamic aphasia: transcortical motor aphasia can also be associated with a specific problem in initiating speech output and the patients can be described as having a motor akinesia (a specific problem in initiating motor acts) (Heilman, 2006). The retention of the Wernicke–Lichtheim link between conceptual representations and speech motor planning would allow this profile of disorder to be accounted for, as would the inclusions of a module to represent the control of intentional speech production (Figure 11.6).

Figure 11.5 Kussmaul’s (1877) model of speech perception and production.

344

Chapter 11 | Disorders of language

J

Intentional system P

Semanticconceptual area I H

O Speech − phonetic movement programs F G

Figure 11.6 Heilman’s (2006) model of speech perception and production.

Q

M

E

Phonological output lexicon D

C

Phonological input lexicon B

A

Motor systems (motor cortex) G

Auditory analysis (STG) A

Speech output

Speech input

Another patient group that is hard for the Kussmal–Wernicke– Lichtheim model to account for is deep dysphasia (Michel and Andreewsky, 1983; Katz and Goodglass, 1990). In deep dysphasia the patients, as in conduction aphasia, make speech production mistakes that include many phonetic errors. The deep dysphasic patients also make errors when repeating, as in conduction aphasia; however, unlike the people with conduction aphasia, who make phonetic errors when repeating words, the people with deep dysphasia make semantic errors. Thus, when repeating ‘duck’, someone with conduction aphasia might say ‘duff’, whereas someone with deep dysphasia might say ‘goose’. When asked to repeat non-words, people with deep dysphasia produce real words that are phonetically similar to the target real words. The original Wernicke–Lichtheim model can account for this profile, as there is a route from conceptual representations to speech motor output control. However, to account for both conduction aphasia and deep dysphasia, it has been suggested that the Kussmal–Wernicke– Lichtheim model needs to split the phonological input lexicon and the phonological output lexicon (Figure 11.6) (Heilman, 2006). The inclusion of separate phonological input and output lexicons provides a way to discriminate between the profiles of problems seen in people who have deep dysphasia and conduction aphasia: in conduction aphasia, people have a potential lesion of line E (Figure 11.6), connecting the phonological output lexicon to the expressive speech output centre (D): this would lead to phonetic errors in speech production and problems with repetition, as in conduction aphasia (Heilman, 2006). In contrast, a lesion of the connections (line C in Figure 11.6) between the phonological input and output lexicons would not prevent repetition, as the input and output lexicons could be connected

11.2 Models of aphasia via the semantic-conceptual centre (I in Figure 11.6). As the semantic-conceptual route is based on ‘real’ words, non-word repetition becomes difficult, as in deep dysphasia. Furthermore, as the semantic-conceptual system does not have access to phonology, frequent semantic errors are made in speech production, as the words selected for output are constrained by semantic, not phonetic representations (Heilman, 2006). The separation of the input and output phonological lexicons also allowed people to account for the problems experienced by a patient (Roth et al. 2006) who made many errors during speech production, with the words produced often being semantically related to the target words. When naming objects, he would often make errors, and was not helped by semantic cues. In contrast, phonetic cues would often help him name more accurately, but he would now make frequent phonological errors. It was suggested that this patient had damage to both whole word and phonetic methods of naming items – and that furthermore, in normal language use, people would use both routes when naming objects. This would link the models to a parallel-distributed processing framework, rather than being limited to serial processing (Heilman, 2006). However, there is a further group of patients who have deficits of confrontation naming – problems in identifying objects by name via prompts. In anomic aphasia, these problems are independent of the modality in which the patients are tested; in optic aphasia, patients have a specific problem when given visual objects to name (Freund, 1889). In visual agnosia, patients have great difficulty not just in recognising and naming objects, but in retrieving semantic information about the objects (e.g. describing how they would be used). In optic aphasia, the problems are limited to naming the object from visual presentation: that is, they might not be able to name a pair of scissors, but they could mimic how they would be used, and describe situations in which they would be used. Their problem can thus be considered a form of aphasia rather than of visual processing or visual knowledge, and has been described as a problem in the link between visual object knowledge and the phonological output lexicon. This has led to a modification of the Kussmaul–Wernicke–Lichtheim model where a module for visual object processing has been included (Figure 11.7) (Heilman, 2006). The opposite profile of deficits has been described in some patients with dementia, who can name objects that they are shown, but not from verbal definitions: this has been termed non-optic aphasia. The patients can repeat words without mistakes, and can name objects correctly because the output lexicon and speech motor systems are intact, as are their object recognition units and their access to the phonological output lexicon. In contrast, normal speech production and comprehension were impaired, including their naming to definitions and their non-optic aphasia was thus linked to degraded semantic representations. This may link to semantic dementia, a focal dementia where the first symptoms are associated with loss of the ability to map between heard words and their meaning.

345

Key Term Dementia A persistent impairment in intellectual function due to brain dysfunction, which commonly is associated with a progressive loss of function. It is mainly a disease of ageing, being more common in more elderly populations. Dementias can be relatively focal in their effects (e.g. semantic dementia) or more widespread and ‘global’ in their effects (e.g. Alzheimer’s disease). Some dementias primarily affect subcortical regions (e.g. Parkinson’s disease) and others have a more cortical effect (e.g. Pick’s disease).

346

Chapter 11 | Disorders of language

J

Intentional system P

K

Semanticconceptual area I

Object recognition units L

H O

Q N

Speech − phonetic movement programs F

E

Phonological output lexicon D

C

Phonological input lexicon B

G

Figure 11.7 Heilman’s (2006) revised model with additional module for visual object processing.

A

Motor systems (motor cortex) G

Auditory analysis (STG) A

Speech output

Speech input

The cognitive neuropsychology approach to aphasia has been tremendously influential in the understanding of aphasia and the ways that human language is implemented in the human brain. There are some limitations to the uncritical application of some of these concepts, however, that are worth considering. In the next section, more detailed aspects of aphasic profiles are considered.

11.3 DETAILED SYMPTOMS OF APHASIC PROFILES BROCA’S APHASIA Patients with Broca’s aphasia have highly non-fluent speech, with difficulties in repetition. There are typically long pauses between words when they speak, and their speech sounds effortful. There is very often a motor speech problem (apraxia) or dysarthria accompanying this. Their comprehension of speech, however, is not compromised. Broca’s aphasia is often associated with damage that extends out of the posterior inferior frontal cortex into surrounding cortex. As primary motor cortex lies next to Broca’s area, patients often have a muscle weakness or paralysis. This typically affects the right (opposite side of the body from the lesion – contralesional) side of the body, as the motor areas on the left side of the brain control the right side of the body, and vice versa. There is not necessarily a correspondence between Broca’s area and Broca’s aphasia. ‘Classical’ Broca’s area, as described by Broca, lies in the posterior third of the inferior frontal gyrus, and encompasses

11.3 Detailed symptoms of aphasic profiles Brodmann’s areas 44/45 (Figure 11.1). However, to have a full clinical profile of Broca’s aphasia, more extensive damage is required. Mohr et al. (1978) looked at twenty lesions at autopsy, and related the clinical speech problems that the people suffered in life to their acquired brain damage. A lesion to Broca’s area itself caused transient speech mutism – a loss of all speech production. This may well have been transient, because of plasticity in the brain, or because the right hemisphere regions start to be recruited. For full Broca’s aphasia, the lesion needed to encompass a lot of the Sylvian region including left opercula, insula, and subjacent white matter in the territory of the middle cerebral artery including Broca’s area. Broca’s original case, which involved damage due to a neoplasm (tumour), which arose due to syphilis, involved these areas. Functionally, the cell structure and anatomy of BA 44 corresponds to premotor cortex, and BA 45 to prefrontal cortex, so it is unlikely that they perform the same processing functions. It is therefore almost certainly the case that Broca’s area is involved in a variety of processes, some motoric, some not. Since the development of functional imaging enabled the investigation of language (and other cognitive, perceptual and motoric functions) in intact, healthy human brains, it has become clear that Broca’s area is engaged by a range of non-linguistic tasks, for example in the representation of task-relevant information, or in non-linguistic aspects of syntax. It is possible that the critical importance of Broca’s area in speech production may therefore result from it having important general cognitive functions in the planning and control of behaviour, for example, response selection (Schnur et al., 2009).

WERNICKE’S APHASIA Wernicke’s aphasia is a disorder of the comprehension of spoken language, and patients can also show poor naming and repetition. Speech output is fluent, although some patients speak with many paraphasias and neologisms, and speech can be (though is not necessarily) highly incoherent. Notably, these patients rarely if ever correct their errors, which suggests they are unaware of their problem, or that their speech makes little sense (the term for this is anosognosia). The patients don’t normally have a hemiparesis, though they may have cortical blindness, which occurs when primary visual cortex is damaged, leading to a visual field defect (e.g. a hemianopia). This indicates a lesion which lies towards the back of the brain. Generally posterior damage means damage to the brain which lies behind the central sulcus (Figure 11.1). Wernicke’s original papers indicate that he was describing the importance of the left superior temporal gyrus (STG) in speech perception. Over the years, however, papers started to especially emphasise the left posterior superior temporal sulcus (STS) as the location of Broca’s area (e.g. Bogen and Bogen, 1976): this perspective almost certainly reflects the fact that most receptive aphasia cases are caused by cardiovascular disease, that is, stroke: strokes follow the anatomy of the blood supply, and in the temporal lobes, the blood supply runs back to front, meaning that strokes are more common at the back end of the

347

348

Chapter 11 | Disorders of language temporal lobes than the front. This means that the posterior STS may be emphasised in Wernicke’s aphasia because of how strokes happen, rather than because of its functional significance in speech perception. It is also the case that a full profile of Wernicke’s aphasia arises from a more widespread left tempero-parietal lesion – and the larger the lesion, the more severe the speech comprehension deficit (Naeser et al., 1987)

CONDUCTION APHASIA In conduction aphasia, there is a disruption of repetition, with preserved (relatively) comprehension and spontaneous speech, though there may be phonemic errors, and the patients can have problems with confrontation naming. There tends to be no associated neurological problem, e.g. hemiparesis is rare; this likely reflects the fact the conduction aphasia is generally caused by small lesions rather than by other problems (e.g. Wernicke’s aphasia). Some patients have a limited right hemianasthesia, or visual field defect, and these patients may have difficulty with moving their face or limbs to command. Following the conventions of the Boston Aphasia Classification System and the Wernicke–Lichtheim model, conduction aphasia is known as a disconnection syndrome because it is assumed to reflect damage to connections between brain areas connecting, for example, the phonological output lexicon to the expressive speech control centre (Figure 11.7). Not long after Wernicke’s original prediction of the existence of conduction aphasia (as a prediction of his model), the arcuate fasiculus (AF) was discovered, and it appeared to be good candidate route for this pathway: the AF is a white-matter tract running from the posterior STG to Broca’s area and this may represent a connection between B and D in the original Wernicke model (Figure 11.3). However, other reports have implicated the cortex in this condition, especially in Wernicke’s area (Mendez and Benson, 1985). More recent electrical stimulation studies have confirmed this cortical involvement. Anderson et al. (1999) worked with an epileptic patient who, when her posterior STG was stimulated, made speech sound errors when speaking, and had impaired repetition, with preserved semantic comprehension. Conduction aphasia may this reflect a disorder of cortical areas important in repetition, rather than a disconnection syndrome. This, in turn, may mean that the left STG is important in speech-motor links as well as acoustic-phonetic processing of speech.

GLOBAL APHASIA In global aphasia, all major language functions are impaired, both in output and comprehension. This tends to follow an extensive lefthemisphere lesion involving Broca’s area and Wernicke’s area. Such large-scale brain damage involves many associated neurological signs: hemiplegia, sensory loss, visual field defects and attentional disturbances such as extinction or neglect. The lesions need not necessarily be large, and they can often spare Wernicke’s area. However, both cortical and subcortical regions tend to be involved.

11.3 Detailed symptoms of aphasic profiles

TRANSCORTICAL MOTOR APHASIA In this disorder, repetition is preserved but comprehension and spontaneous speech compromised, the latter strikingly so. The repetitions can be mandatory, which is termed echolalia, and can lead to rather disturbing speech patterns. The patients can correct errors in what they are asked to repeat. Spontaneous speech is stumbling, and stuttering, agrammatical and simple. These neurological signs are similar to Broca’s aphasia. The locations of the underlying lesions are variable, and are frequently found anterior and superior to Broca’s area, in the superior anterior frontal lobe. If the patients have problems with accessing semanticconceptual representations when speaking, their lesions are associated with lateral prefrontal cortex, superior to Broca’s area: if they have more of a problem in initiating the motor act of speech, their lesions are associated with midline premotor speech areas (Heilman, 2006).

TRANSCORTICAL SENSORY APHASIA (TSA) In this disorder there is impaired comprehension, preserved repetition and fluent output. Words can be included in the speech output which have been overheard, but which have not been understood. Such ‘repetition’ is again often mandatory, i.e. the patients are echolalic. Kertesz et al. (1982) carried out a study into the localisation of the lesions, and found two sites associated with TSA, in the medial inferior ventral temporal lobe, and anterior STG.

MIXED TRANSCORTICAL APHASIA (ISOLATION APHASIA) In this disorder only repetition is preserved – both comprehension and spontaneous speech are compromised. There is no voluntary language use, and the associated neurological signs are very variable. Some have a bilateral paralysis, leading to quadriplegia or quadriparesis, or unilateral signs, such as a right hemiplegia. There is often a sensory loss. A post-mortem study indicated that anterior and posterior brain damage was involved (Geschwind et al., 1968), and a study by Ross (1980) showed involvement of the left motor and sensory cortices, as well as parietal lobe involvement.

ANOMIC APHASIA Word-finding difficulties are the most prominent feature, leading to speech which can be ‘vague’ and imprecise in content. Most cases of anomic aphasia have no associated neurological signs, and it has been regarded as non-localising as no one area is shown to be implicated in patient studies. Gloning et al. (1963) found that 60 per cent of their patients had temporal-parietal lesions, but the other 40 per cent were wide ranging, though all in the left hemisphere.

PURE WORD DEAFNESS Pure word deafness is very rare. Patients can sometimes tell spoken words from non-speech sounds, others cannot, but none of them can understand spoken words at all. Speech output can be disordered, and

349

350

Chapter 11 | Disorders of language patients cannot repeat or write to dictation. Pure word deafness was first described as a lesion of white-matter tracts into the left auditory cortex (e.g. into A in Figure 11.3). However, more recent work has shown that cortical areas, often on both the left and right sides of the brain, are strongly implicated in pure word deafness. Auerbach et al. (1982) suggested that word deafness due to loss of prephonological auditory processing is associated with bilateral temporal lobe lesions, but that a unilateral left temporal lesion causes word deafness due to a deficit in phoneme discrimination and identification. Another clinical and psychophysical study of a patient does not support this, however; the patient had an initial infarction of the left dorsolateral temporal lobe and presented with Wernicke’s aphasia, but subsequently developed word deafness after a right temporal infarct (Praamstra et al., 1991). Loss of spoken word comprehension only occurred after the second, right-hemisphere infarct. Thus bilateral damage seems to be necessary for ‘pure’ word deafness – this may be a result of plasticity processes in the right hemisphere which support the recovery of some spoken word comprehension. Consistent with this view, more recent overviews have indicated that pure word deafness is seen after unilateral left temporal lobe damage, and bilateral temporal lobe damage, but not after unilateral right temporal lobe damage (Griffiths et al., 1999).

PHONAGNOSIA Phonagnosia is a disorder in which people are unable to recognise other people by their voices. This is not a speech perception problem per se, but as we saw in Chapter 10, we do adapt to idiosyncracies of speech production in a speaker-specific way, so it is not irrelevant to consider this issue. Phonoagnosia is rare, though this may reflect the fact that we are not good at recognising speakers by their voices alone. It may also reflect the fact that many interactions we have with other people are face to face, and hence other sources of information are available; if the voice alone is presented (e.g. on the phone) people commonly introduce themselves. Patients with phonagnosia can recognise people by their faces, and do not have a more general problem with person identity knowledge. They do not have a disorder of speech perception, instead having a specific difficulty in recognising people from their voices. Phonagnosia associated with damage to the brain has been linked to damage to the right temporal lobe. A recent description of a developmental case of phonagnosia – someone with no known brain damage, who had experienced difficulties with identifying voices all her life – revealed no lower-level auditory-processing deficits, nor problems with the perception of other kinds of information from the voice, for example, emotional vocalisations. Instead her problem seemed to be limited to detecting speaker identity cues from the voice (Garrido et al., 2009).

DYSARTHRIA Dysarthria is an acquired disorder of speech production, and refers to a difficulty in the implementation of speech plans, when these are

11.4 Psychological and psycholinguistic aspects of aphasia applied to the movement of muscles. Dysarthria is a specific problem with moving the articulators, due either to problems in the brain in the areas which directly control articulatory movements (e.g. damage to primary motor cortex) or to the cranial nerves which directly activate the muscles (the nerves which are sending the messages from the brain to the muscles). Either of these are routes to muscle weakness in the articulators, and dysarthria. In dysarthria, speech can be mumbled or indistinct, or slurred.

SPEECH APRAXIA Speech apraxia is a disorder of the motor control of speech, in the absence of motor weakness. People with speech apraxia have great difficulty saying what they want to say, and they can be very inconsistent in their speech – a word may be accurately produced on one occasion but not on the next. Patients may be visibly groping for the right word. Their speech can have disordered rhythm and prosody. Patients with speech apraxia commonly have damage to the left anterior insula, which lies medial to Broca’s area in the left inferior frontal gyrus (Dronkers, 1996).

PROSODY PRODUCTION AND PERCEPTION Ross and Mesulam (1979) described two patients who had problems not with the production of spoken language per se, but with the production of appropriate melodic inflections to their speech: this had negative effects on their interpersonal interactions and relationships (Ross, 2000). In contrast, their ability to perceive prosody in speech was not affected. Both patients had right fronto-parietal lesions, and a role for the right frontal lobe in the control of speech prosody has been confirmed since (Gorelick and Ross, 1987; Ross, 1981; Ross and Monnot, 2008). In contrast, patients with damage to the right temporal lobe often have difficulty understanding the meaning of melody in heard speech. It is not unusual for right temporal lobe lesions to be relatively ‘silent’, because they do not often lead to frank language problems. However, on direct testing, patients with right temporal lobe lesions often show problems understanding the melody of spoken language, and this can extend to problems with other kinds of melody processing, for example in music.

11.4 PSYCHOLOGICAL AND PSYCHOLINGUISTIC ASPECTS OF APHASIA The clinical basis of aphasia studies has necessarily focused on issues of symptoms and diagnosis, rather than on more conceptual aspects of language use. However, we know that speech perception and production, as discussed in Chapter 10, involve phonetic, lexical, semantic

351

352

Chapter 11 | Disorders of language and syntactic aspects. Can we see these selectively damaged in clinical language problems?

PHONETIC DEFICITS A problem of phonetic processing has direct and dire consequences for the comprehension of spoken language – a patient will be unlikely to have a deficit in perceptual speech processing that does not impact on lexical and semantic/syntactic processing. However, the locus of phonetic processing seems to correspond to lesions to the STG/STS (i.e. Wernicke’s area).

SYNTACTIC DEFICITS Agrammatical patients, who have a problem producing grammatically correct sentences, often have speech which is telegraphic and in which function words are omitted. They can have specific problems with passive constructions. Many of these patients (but by no means all) may have a Broca-like aphasic profile. Notably, patients with agrammatical speech also always have a motor speech problem – an apraxia or dysarthria of speech, for example, or (more rarely) foreign accent syndrome, where people’s accents sound very changed to their fellow countrymen (due to the way we listen to and label accents, rather than the acquisition of a new accent). This suggests that syntactic processing and representations in speech production are closely linked to speech motor acts. Importantly, Varley and colleagues (Varley et al., 2005; Varley and Siegal, 2000) have demonstrated that densely agrammatical patients can still perform other kinds of tasks accurately, including logical, mathematical and social cognitions (theory of mind tasks), suggesting that the disorder of syntax does not necessarily affect other kinds of complex cognitive processes.

SEMANTIC DEFICITS As can be seen in aphasia, there is a variety of different ways that semantic processing can be compromised; however, the purest form seems to be seen in semantic dementia (see also Chapter 7), a focal dementing disorder which, unlike more global dementias like Alzheimer’s disease, is associated with specific loss of grey matter in (initially) quite restricted cortical fields. In semantic dementia, the first symptom is a difficulty understanding the meaning of spoken words, and the damage is seen in the left anterior and ventral temporal lobe. The patients can understand what objects are, and use them appropriately, and their phonetic and syntactic performance is unimpaired. As the disease progresses, the patients start to make phonetic errors, suggesting that phonological processing is being compromised, and it has been suggested that severe problems in speech output are seen when the disease spreads to the right temporal lobe. Semantic dementia has therefore, in its initial stages, been identified as a selective semantic-processing deficit, and the left anterior temporal lobe has therefore been identified as a candidate location for amodal semantic representations, and thus potentially the central ‘hub’ in the hub model of semantic representations (Patterson et al., 2007).

11.5 Functional imaging of human language processing

11.5 FUNCTIONAL IMAGING OF HUMAN LANGUAGE PROCESSING We now have access to functional-imaging data, which complements our understanding of the neural basis of language processes based on patient studies. Functional-imaging techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) allow one to identify activity associated with a particular activity (e.g. speech perception) and also to localise the activity at the level of gyral anatomy, rather than neurons. This makes PET and fMRI particularly useful for investigating language processing in the healthy human brain, and to compare these results with the profiles seen in patients.

SPEECH PERCEPTION Possibly because of the long established use of neurocognitive models in the study of aphasia, and the links between structure and function which have been made from patient studies, speech and language were two of the first phenomena to be studied with functional-imaging techniques, such a PET or fMRI. Importantly, all functional-imaging studies show patterns of relative activation, where the activation seen is relative to that seen in some kind of baseline contrast, so it is always important to identify what the contrasted conditions are in a PET or fMRI study.

A STUDY OF SPEECH PERCEPTION USING PET Early functional-imaging studies showed that the perception of speech led to extensive bilateral activation in both the left and right superior temporal gyri compared with silent rest. Of course, heard speech is an acoustic signal, so to see activation specifically associated with speech, we need to control for activation associated simply with ‘hearing a sound’, for example, in primary auditory cortex. In addition, speech is an immensely complex acoustic signal, so we need to control for some aspects of acoustic complexity, without making a sound that is in any way intelligible. A study by Scott et al. (2000) attempted to do this with two forms of comprehensible speech. The design was a conjunction design, where the aim was to identify cortical responses to speech in a way that was independent of what the speech sounded like, while controlling for the complexity of the speech signal. 1. Non-speech stimuli. Spectrally rotated speech was used, in which the speech signal is ‘turned upside down’ in the frequency domain, creating a stimulus which contains all of the original speech signal, but which cannot be understood. Spectral rotation preserves the amplitude envelope and the pitch of speech sounds, so these rotated stimuli have preserved prosody, rhythm and syllabicity of the speech without comprehension being possible (Blesser, 1972); it thus forms an appropriately complex non-speech contrast. 2. Intelligible speech. Two forms were used: normal, clear speech and noise-vocoded speech, which sounds like a harsh whisper, and

353

Key Term Positron emission tomography (PET) A method of imaging structure and function in the human brain by directly tracking blood flow using radioactive tracers. PET can be used to form structural images of blood flow in the brain, as the brain is richly supplied with blood. PET can also be used to look at neural activity by tracking local changes in regional cerebral blood flow, which are seen when there is local increased in neural activity. Because the power of PET is limited by the number of scans, and because the number of scans is limited by the amount of radioactivity which can safely be administered, PET is becoming less commonly used for functional imaging studies. Functional magnetic resonance imaging (fMRI) A medical imaging technology that uses very strong magnetic fields to measure changes in the oxygenation of the blood in the brain and thus map levels of activity in the brain. It produces anatomical images of extremely high resolution.

354

Chapter 11 | Disorders of language which is a simulation of what someone who uses a cochlear implant can hear. The noise-vocoded speech does not sound like a recognisable person: it is intelligible but the listener cannot tell if they are listening to a man, a woman or a robot. Essentially, noise-vocoded speech lets us create a speech stimulus with little associated speaker information (of course, this is an obligatory aspect of normal speech, where we hear speech but also hear someone speaking, their gender, their age, their mood etc.). 3. Conditions. The conjunction design meant that there were four conditions: clear speech, noise-vocoded speech, rotated speech and rotated noise-vocoded speech. The design aimed to identify brain areas which were activated by both speech over rotated speech, and noise-vocoded speech over rotated noise-vocoded speech. The task was passive listening, and the eight subjects were all familiar with the stimuli. The left superior temporal gyrus was strongly activated by the rotated speech as well as the intelligible clear and rotated speech. This is consistent with other studies implicating the STG in the processing of acoustic structure (e.g. Hall and Johnsrude, 2002). Other studies have indicated that there is complex processing of phonetic information in the left STG, with sensitivity here to linguistically relevant changes, relative to acoustic changes (e.g. Jacquemot et al., 2003). Further studies have indicated that properties of phonemes are represented in the left STG (Obleser et al., 2006 ), and that consonant-vowel combinations are selectively represented just below this, in the left STS (Liebenthal et al., 2005). There is also evidence that syntactic and semantic information is processed in the left STG: a study explicitly contrasting semantic and syntactic violations in spoken sentences reported common activations to semantic and syntactic violations in the left STG (Friederici et al., 2003). It is thus likely that there is massively parallel processing of spoken language in the superior temporal gyrus and sulcus, including semantic and syntactic processing as well as phonetic processing. This would be consistent with some of the evidence shown in Chapter 10 that the phonetic and acoustic realisations of spoken language vary systematically with semantic and syntactic features. When the intelligibility conjunction was performed, to isolate cortical responses to speech which can be understood, over and above any processing dependent on the acoustic structure of the stimuli, a region in the left anterior superior temporal sulcus was identified as sensitive to intelligible spoken sentences, whether or not they were noise-vocoded or clear (see also Evans et al., 2013). This indicated that we can identify a cortical response in the left anterior temporal lobe to comprehensible speech, over and about its acoustic complexity. However, as whole sentences were used, we cannot dissociate which elements (phonetic, semantic, syntactic, lexical) have contributed to this response, although it is almost certain that all factors do. A further fMRI study (Cohen et al., 2004) used the repetition of spoken words to investigate where the ‘auditory word form’ area lies:

11.5 Functional imaging of human language processing

355

auditory word forms are representations of the heard speech which are speech specific and not driven entirely by the acoustic signal. In this study, repetition suppression was used – the fact that a repeated stimulus will result in a reduction in the cortical response, while a change in stimulus properties to which a particular brain area is sensitive will not result in reduced activation. This study played people words, either novel or repeated, and found that the left anterior STS is the first point in the temporal lobes where there is significant suppression to repeated words, and enhanced responses to novel words (Cohen et al., 2004). The left anterior STS is well placed between auditory areas and the left anterior lobe ‘hub’ for semantic representations (Patterson et al., 2007), to form well-specified auditory representations of heard speech. In contrast to a left anterior dominance in processing speech for meaning, posterior superior temporal lobe regions appear to be important in the processes subserving repetition, with posterior temporal lobe (and inferior parietal) fields being selectively involved in verbal fluency tasks (Price et al., 1996), the silent rehearsal of non-words (McGettigan et al., 2011) and vocal sound-to-action links (Hickok et al., 2000; Warren et al., 2005). This is consistent with an anatomical focus for the posterior STS in conduction aphasia, which is a specific disorder of verbal repetition. The striking factor about all of these complex processes which translate between the sounds of speech and words in the brain is that they are all, anatomically, falling within the regions in the left STG originally described by Wernicke (Figure 11.8). Thus ‘Wernicke’s area’ subsumes a range of different anatomical areas and functional properties, from acoustic/phonetic to semantic and syntactic, all of which underlie normal ‘speech comprehension’. This probably results from considerable parallel processing of the properties of heard speech input. Outstanding questions concern the extent to which these processes involve the identification of phonemic structure, or of higherorder sequential structure over groups of phonemes. There is also

Peak responses to repetition processes Primary auditory cortex

Anterior

Peak responses to intelligibility Temporal pole

Posterior

Figure 11.8 Diagram of the brain showing areas responding to repetition and intelligibility.

356

Chapter 11 | Disorders of language considerable interest in the extent to which there may be phoneme ‘maps’ in the STG, where phonemes are coded in terms of their features (e.g. Obleser et al., 2006).

THE NEURAL BASIS OF CONTEXT EFFECTS IN SPEECH PERCEPTION Context has a huge effect on speech processing. People find it easier to identify phonemes in a word than in a non-word, to recognise a word if it is in a sentence, and to understand a sentence if it is predictable than if it is unpredictable in content. Obleser et al. (2007) used fMRI to identify how linguistic context supports speech comprehension. They contrasted sentences like: The ship sailed across the bay. Sue discussed the bruise. The former is very easy to understand, as there is a lot of contextual support, both semantic and syntactic, for the sentence. The second sentence is harder to understand, as there is no contextual support to help, unless one knows Sue and her particular tendencies to discuss these things. These effects can be seen in clear speech comprehension, and become very important if the speech is presented in noise, or if the listener has a hearing impairment. Obleser et al. degraded spoken sentences to make them harder to understand, such that context could have an effect, and presented these to people whose neural activity was monitored using fMRI. When the conditions where the effects of context had the greatest impact on comprehension were investigated, the contrast of predictable sentences over unpredictable sentences revealed a distributed lefthemisphere system, all outside the left temporal lobe, with activation in the inferior and superior frontal gyri, angular gyrus and posterior cingulate. This suggests that a wide sematic network is recruited to support speech comprehension, and that this has great impact when context can be used to enhance understanding.

REHEARSING NON-WORDS VERSUS LISTENING TO NON-WORDS One of the most basic findings in working memory research is the word length effect – the longer the verbal items being transiently stored, the fewer the items that can be stored accurately (e.g. Caplan et al., 1992). McGettigan et al. (2011) addressed this in a study of the rehearsal of non-words, which varied both in duration (two or four syllables) and in phonetic complexity (no consonant clusters versus two consonant clusters). This led to four conditions: two syllables, no consonant clusters (e.g. fipul); two syllables, two consonant clusters (e.g. frispul); four syllables, no consonant clusters (e.g. fotumipul); and four syllables, two consonant clusters (e.g. frotumispul). In two separate fMRI experiments, two different sets of participants were asked

11.5 Functional imaging of human language processing to either rehearse the non-word prior to repeating it, or to listen to it passively, with no overt response. In the passive perception task, the increasing duration of the nonwords was associated with bilateral activity in the superior temporal gyri, running back from the primary auditory cortex into the posterior temporal lobes. This difference from the responses normally seen to speech may reflect the fact that these non-words have no (or little) semantic or syntactic content. Unlike the strong response to non-word duration (in syllables), there was no sensitivity to the consonant clusters in the STG responses, suggesting that there is a less marked sensitivity to individual phonemes in STG than to syllables. In the rehearsal experiment, there was also bilateral STG activation to the four-syllable non-words relative to the two-syllable non-words: this activation extended into left premotor cortex, and towards Broca’s area on the left. During silent rehearsal of non-words, motor systems are recruited. Furthermore, these premotor fields were sensitive to the presence of consonant clusters, indicating a role of individual phonemes in the planning of motor speech output. In addition to showing the relationship between the articulatory loop and brain regions critical to articulation during the rehearsal of non-words, this study shows different sensitivities in perceptual and motor systems to aspects of spoken words. Phonemes may thus form distinct segmental representations in speech production processes, rather than in speech perception processes.

NEURAL BASIS OF SPEECH PRODUCTION The neuroanatomy of speech production varies, as might be expected, with the kinds of speech production tasks used. Simple repetition, for example, has been shown to be associated with activation of the left anterior insula, but not Broca’s area. This is consistent with a role for the left anterior insula as the locus of damage in speech apraxia (Dronkers, 1996), and suggests that when speech production is simple (one word) and completely specified (the participant is told the word to repeat directly before it is repeated) then Broca’s area need not be recruited (Wise et al., 1999). This finding is consistent with the left anterior insula being closely associated with the control of the articulators, and Broca’s area being associated with higher-order functions, including response selection and grammatical sequencing of output. Consistent with this suggestion, Broca’s area increases in activity if the speech task is made more complex. Another study of speech production contrasted counting aloud, reciting a well-learnt nursery rhyme, and generating propositional speech (responding to questions) with a baseline condition in which participants listened out for occasional noises (Blank et al., 2002). Counting aloud involves producing words according to simple grammatical principles, as the numbers increase: the spoken numbers themselves form normal speech production, but with a highly constrained semantic and syntactic palate. The very familiar nursery rhymes are similarly constrained (there is no room for improvisation), though there is a far wider range of semantic

357

358

Chapter 11 | Disorders of language

Key Term Alexia/dyslexia Both refer to problems in reading written language. Alexia always refers to acquired difficulties in reading, while dyslexia is used to refer to developmental difficulties in reading. However, dyslexia is also used to refer to particular profiles of acquired reading problems, e.g. deep versus surface dyslexia.

and syntactic structure. The propositional speech, in which people generated speech in response to questions such as ‘tell me about a relative you know well but do not live with’, is relatively unconstrained: while the participant might be reasonably expected not to start to discuss the economic state of the euro, it is up to them if they discuss a brother, parent or cousin, and beyond that, whatever aspect of that person that they’ve decided to discuss. This means that in generating the speech, in addition to having a yet wider possible range of semantic and syntactic content than either nursery rhymes or counting, the participant has a lot of pragmatic decisions to make about what would constitute an appropriate answer. A portion of Broca’s area, the pars opercularis, was least activated by the counting condition, more activated by the nursery rhymes condition, and most activated of all by the propositional speech. The contrast of propositional speech over the counting and nursery rhymes conditions showed extensive activations, beyond Broca’s area. There was activation in the left anterior temporal lobe, medial prefrontal cortex, left angular gyrus and posterior cingulate. These indicate the recruitment of a distributed semantic system to support the linguistic and memory components of normal conversational speech. It is striking that these activations are extremely similar to those seen in the study of the use of context in speech comprehension (Obleser et al., 2007): this suggests that the same semantic/memory system is implicated both in speech production and perception, as would be predicted by the Kussmaul–Lichtheim–Wernicke model of aphasia (Figure 11.7). During speech production, there is commonly a deactivation in the left mid STG/STS associated with listening to one’s own voice. This may reflect a general reduction in sensory responses to self-generated stimulation – a very similar reduction in self-generated touch sensations has been suggested to underlie the fact that you cannot tickle yourself (Blakemore et al., 1998).

11.6 READING Both functional-imaging and patient studies indicate a distributed network of activations associated with reading, and these can be distinguished by their involvement in either word recognition and comprehension, or eye movements.

VISUAL WORD RECOGNITION The primary visual cortex nestles in the calcerine sulcus, on the medial aspects of the occipital lobes. Lateral and ventral to this, is a cortical field on the inferior surface of the left occipital lobe which has been associated with the visual processing of words – a visual word form area (VWFA) (Figure 11.9). This region, if damaged, is associated with a dense alexia – a problem of reading words. Patients can typically use other kinds of visual symbols, e.g. do maths. The precise function of

11.6 Reading

359

Temporal pole

Fusiform gyrus

Visual word form area

Primary visual cortex

the VWFA remains controversial – for example, subtle problems with visual object processing can be seen in patients who have reading deficits following a lesion to this area, and it has been argued that reading is such a recent human development that it is unlikely that evolutionary processes have affected the brain’s processing in this way (Price and Devlin, 2003). However, it is clear that the left inferior occipital lobe is important, indeed critical, to the early perceptual processing of written language.

NEURAL CONTROL OF EYE MOVEMENTS The movements of the eyes (called saccades) across text are extremely precise and reflect a great deal of processing of the upcoming visual information – i.e. the upcoming text, which is to the left of the word currently fixated upon during reading (Rayner and Bertera, 1979). This is processed in such a way that, not only are the following saccades accurate, but they are not made onto every word – typically, for example, people do not saccade to a function word. I LOVE TO SEE THE THE RED SUN AND THE THE NEW DAWN OF OF ANOTHER MORNING

Figure 11.9 Diagram of the brain showing area associate with visual processing of words.

360

Chapter 11 | Disorders of language ‘Illusions’ like the paragraph above (ask someone to read it aloud and see how many times they say ‘the’) occur precisely because we do not saccade onto every word in a sentence, so we don’t notice if a function word is repeated. Likewise, count the Fs in the following sentence: FRIENDS OF MINE HAVE FOUND FINE COMFORT FROM THE SIGHT OF HOME It’s not unusual for people to report back three or four F’s, but in fact there are seven Fs in that sentence. The illusion occurs because when reading we do not saccade to every word, but skip the function words such as ‘of’. It is therefore harder to see the Fs in these words. The planning of saccades is based on visual information in the left visual field (Figure 11.10), in the surrounding parafoveal regions where there is less precise resolution of the visual world, while the word which is being fixated upon (and onto which the last saccade landed) is being read (Rayner and Bertera, 1979). There thus has been interest in the extent to which reading requires letter-by-letter processing, or whole-word processing, and the general consensus is that whole-word processing dominates. This means that sentences such as the following can be read: FI YOU ASY HTAT OT EM AIGAN TEHN I HVAE ON OTPOIN BTU OT LAEVE The role of parafoveal space in planning upcoming saccades across text means that there is a second kind of alexia, which is associated with problems reading words in a sentence. This is seen in patients

Figure 11.10 The control of saccades.

11.6 Reading

361

who have a deficit in their right visual fields, and a consequent lack of visual information about the upcoming words that can be used to plan saccades. These patients can often read a word presented to them in a letter-by-letter fashion, sounding out ‘cat’ as C, A and T. They have tremendous problems in reading connected text, because they cannot see the upcoming words. Thus a motor problem (difficulty planning eye movements to the next words in text) can result in a frank reading difficulty (Zihl, 1995).

ROUTES TO READING Research has established the important concept of different potential routes for reading – for example, skilled adult readers can either read a word by sounding out the letters or by recognising the whole word, and when they encounter a new or a difficult word they may emphasise one way of reading more than another. The early diagrams incorporating the disorders of spoken language that we saw earlier in this chapter have also been developed to account for acquired problems in reading and writing. Acquired dyslexia (sometimes called alexia) refers to a problem in reading which has its onset after the skill of reading has been achieved, and acquired agraphia refers to a problem in writing which occurs after people have learnt to read. Both agraphia and acquired dyslexia are associated with brain damage, often stroke or dementia. As in spoken language, acquired problems with writing tend to group into non-random profiles of difficulties, and these have been specifically modelled along similar lines to the models of aphasia discussed earlier: some models even manage to encompass both speech and writing disorders in the same model (Ellis and Young, 1996) (Figure 11.11). Tests of reading often focus on whether words are ‘real’ words or non-words, or whether they are regularly spelled, or whether they are frequently encountered (high or low frequency), and their grammatical status (e.g. function words versus content words).

SURFACE DYSLEXIA Some patients can only read words if they can sound them out first, and tend to be better with regular than irregular words – for example, they might produce an irregular word like ‘pint’ as if it was pronounced like ‘hint’. Only after they have said the word aloud do the patients understand the meaning. This is known as surface dyslexia and is associated with damage to the temporal lobes (Deloche et al., 1982). In surface dyslexia, there is considered to be damage between the visual representations – the visual word forms – and the wider semantic system. This means that the patient cannot rely on a mapping between the visual word form and semantics to access the meaning of a word, but will need to utilise the connections between graphemic and phonemic representations. This can be considered as a problem dealing with the ‘whole word’ route for reading, which forces the patients to rely on sequences of individual letter to access the pronunciations, and then the meanings, of the words.

Key Term Dyslexia Developmental difficulties in reading (see also alexia above).

362

Chapter 11 | Disorders of language

SPOKEN WORD

WRITTEN WORD

Auditory analysis

Visual analysis

Auditory input buffer

Orthographic input buffer

Auditory input lexicon

Graphemic input lexicon

Sub-word level auditory to phonological conversion

Phonological to auditory conversion

Figure 11.11 A neuropsychological model of the processing of spoken and written language.

Cognitive system

Phonological output lexicon

Phonological output buffer

Sub-word level orthographic to phonological conversion

Graphemic output lexicon

Sub-word level phonological to orthographic conversion

Sub word level graphemic-toorthographic conversion

Graphemic-toorthographic conversion

Graphemic output buffer

Speech production Writing

Source: Adapted from Ellis and Young (1996).

PHONOLOGICAL DYSLEXIA In phonological dyslexia, patients can read words which are both real words and familiar words (i.e. words known to them) but struggle with non-words (Shallice and Warrington, 1980; Ellis and Young, 1996). One such patient could read a list of content words with high levels of accuracy (95 per cent correct, including uncommon words like ‘decree’ and ‘phrase’, but was able to read only 8 per cent of a list of matched nonwords (Patterson, 1982). When confronted with a non-word, for example ‘soof’, he would often read it as a real word (e.g. ‘soot’) – importantly, these errors with non-words typically involved the production of a visually similar real word. Unlike the surface dyslexia patients, who have damage to the lexical-semantic route for reading, but access to graphemeto-phoneme conversion routes, patients with phonological dyslexia are thought to have damage to grapheme-to-phoneme conversion routes, which forces them to read via lexical-semantic pathways. This works well when they encounter familiar words, but causes problems when a word is unfamiliar, as they cannot use grapheme-to-phoneme conversion strategies to support reading these new words accurately.

DEEP DYSLEXIA Marshall and Newcome (1966) described a patient with ‘deep’ dyslexia, who when reading made a large number of errors – around 50

11.6 Reading

363

per cent - but these errors were often semantically related to the target word (e.g. reading ‘abroad’ as ‘overseas’). Other errors made by patients with deep dyslexia include reading non-words as real words (e.g. reading ‘tweeps’ as ‘sweet’), and visual errors (e.g. reading ‘nightmare’ as ‘night’); the list of errors seen is longer (up to twelve different kinds of errors have been described) (Plaut and Shallice, 1993). In contrast, these patients can be surprisingly good at some other kinds of tasks – for example, many patients can perform lexical decision tasks quite accurately (Coltheart, 1980). Deep dyslexia has been described as arising from damage to both grapheme-to-phoneme routes, and to lexical-semantic pathways, as well as visual-processing problems (Morton and Patterson, 1987). Unlike many of the other kinds of language problems discussed in neuropsychological research, the variety of problems seen in deep dyslexia is harder to account for by referring to relatively simple ways of damaging a ‘box and arrow’ model of language (Coltheart et al., 1987). That being said, the profile of problems associated with deep dyslexia co-occur with such consistency that the disorder reflects a consistent and coherent kind of language problem. One account for deep dyslexia, which often follows left temporal lobe damage, is that it reflects the reading capabilities of the right hemisphere (Coltheart 1980, 1987; Saffran et al., 1987). In this approach, left-hemisphere systems underlying lexico-semantic and graphemeto-phoneme conversion have been damaged, but right-hemispheric mechanisms can still process some aspects of words and associate the words with semantic representations. This is argued to account for the semantic errors, as the right hemisphere is considered to be less precise in its semantic associations: it also accounts for the problems with function words and abstract words, as these are considered to be less well represented in the right hemisphere. Non-words cannot be read as they cannot access the intact semantic system(s). Following semantic activation, preserved speech output systems in the left hemisphere are recruited to support speech production. Another approach to deep dyslexia is a connectionist model, developed by Hinton and Shallice (1991) (see also Plaut and Shallice, 1993). This model (Figure 11.12) used three processing levels (grapheme, intermediate and semantic, plus a ‘cleanup’ level)

S⇒C 60 cleanup units

68 sememe units C⇒S

I⇒S 40 intermediate units G⇒I 28 grapheme units

Figure 11.12 The network used by Hinton and Shallice. Notice that sets of connections are named with the initials of the names of the source and destination unit groups (e.g. G–I for grapheme-to-intermediate connections).

364

Chapter 11 | Disorders of language The model contained a semantic network in which semantic associations between words (from a limited possible set of words) was represented, across a number of different semantic parameters: the network was trained (using back propagation) on a set of words, after which it could map between written words to the correct semantic meaning. Plaut and Shallice then systematically lesioned the model, in terms of location of damage and severity, to identify patterns of errors that arose. They classified four different error types: 1. 2. 3. 4.

visual (cat > cot); semantic (cat > kitten); visual-semantic (cat > rat); other (cat > mug).

All lesions were noted to lead to visual, semantic and visual-semantic errors at higher rates than random variation would predict. There was also a tendency for damage nearer the input layer to lead to visual errors, and damage nearer to the semantic layer to lead to semantic errors. However, errors characteristic of deep dyslexia were found following all the lesions. Thus deep dyslexia was an early demonstration of the power of a connectionist approach in accounting for patterns of damage in neuropsychological research.

FUNCTIONAL-IMAGING STUDIES OF WRITTEN LANGUAGE As might be expected from the above sections, functional-imaging studies have shown the activation of the ‘visual word form area’ in the left lateral occipital lobe when visual words are silently read, and the recruitment of posterior parietal areas and frontal eye fields associated with the control of eye movements during the reading of text. These seem to be brain areas specifically associated with written language rather than heard speech, although they may not be specific to only written language (Price and Devlin, 2003). The acquisition of written language is parasitic on speech perception and production: while we learn to understand and produce spoken language without overt instruction, learning to read and write is something we need explicit instruction in, and which is something which is much harder for us to do it we had not learnt to understand a spoken language first. We might therefore expect considerable overlap between neural regions that support the processing of visual and spoken language perception. Functional-imaging studies have confirmed this relationship, by showing, for example, that both heard and read stories (each relative to a complex perceptual baseline) are associated with activation in the left superior temporal sulcus, and with activation in areas associated with amodal semantic representations running along the bottom of the left temporal lobe, and the left anterior temporal pole (Spitsyna et al., 2006). If the reading task requires people to sound out the letters, then this can result in extra activation in premotor and supplementary speech areas; indeed, if readers are commonly reading by sounding

11.7 Developmental disorders of language out the letters, this will be often indexed by activity in the midline supplementary speech area. This represents ways of using articulations to access word forms, letter by letter.

11.7 DEVELOPMENTAL DISORDERS OF LANGUAGE In addition to speech and language problems that are associated with damage to the brain – known as acquired disorders of speech and language – there are a variety of language problems that are a result of difficulties which are present from very early in life, and which are not associated with known incidents of acquired brain damage. These are generally known as developmental disorders, and they have some similarities and some important differences from the profiles seen in acquired damage. Key to the concept of developmental disorders is the need for the identified problem to be relatively more severe than the child’s other abilities – for example, if the child has poor verbal IQ on tests, they will only be considered to have a specific language problem if their verbal IQ score is much poorer than their non-verbal IQ score.

DEVELOPMENTAL DISORDERS OF SPEECH PERCEPTION AND PRODUCTION – SPECIFIC LANGUAGE IMPAIRMENT Specific language impairment (SLI) is a developmental disorder of language in which children show problems with spoken language comprehension and production, problems that are disproportionate to their non-verbal IQ. Furthermore, their language problems are not a consequence of brain damage, hearing loss, or deprivation. The speech of children with SLI can be hard to follow, as they can find it hard to express their ideas, and their speech can sound muddled and underarticulated; they use sentences but what they say can be difficult to understand. When they listen to other people, children with SLI can themselves find it hard to understand what is said, and find it hard to do what someone asks them to do. Their vocabulary can be restricted to a relatively small set of words, and they can find it hard to repeat words and sentences. These difficulties make it hard for children with SLI to cope, both in formal educational settings, and in interactions with their peers (e.g. when playing), unless support is provided for them. The condition can vary in severity, with some children experiencing relatively mild problems, and other children having much more severe difficulties: an eight-year-old child with relatively severe SLI might be producing speech typical of a three-year-old (e.g. ‘me go there’ rather than ‘I went there’) (Bishop 2006). In terms of the underlying problem, there are three general theories of SLI. The first is that the children have an underlying auditory processing deficit, and their problems in processing sounds (e.g. in telling the order in which two sounds are played) can have a profound impact on their ability to hear speech, and a knock-on effect on their

365

366

Chapter 11 | Disorders of language ability to produce speech. The second theory is that they have a particular problem with verbal short-term memory, and can find it hard to repeat non-words; this problem would lead to the children finding it hard to say and learn new words accurately. The third theory is that the children have a specific deficit in processing syntax, which leads to them having particular problems in hearing and producing syntactic properties of speech. The idea of a developmental disorder of syntax attracted a great deal of interest from people interested in the ideas of Chomsky and a universal grammar (Chapter 10). Similarly, there was a lot of interest in the auditory processing deficit model, since it would avoid the positing of specific linguistic mechanisms. If a general auditory-processing deficit were primarily manifest as a language deficit, this might be evidence against a universal grammar perspective. Specific language impairment has a strong genetic component, being highly heritable; however, it has a complex profile of heritability, like asthma or diabetes, and does not show a simple pattern characteristic of a dominant or recessive genetic contribution. Instead, multiple genes seem to be involved. Work by Dorothy Bishop has indicated that there are separable genetic contributions to the problems with syntax and non-word repetition tasks shown by children with SLI. In contrast, their problems with rapid auditory processing have a strong environmental contribution, being primarily associated with whether or not there is a musical instrument in the home. These data suggest that SLI is not only a complex and variable disorder, but that there are separable contributions of problems with syntax processing and verbal working memory, as well as potential environmental issues. SLI may form an extremely important case for investigating the ways that genes and environment interact in language development and disorders (Bishop, 2006).

DEVELOPMENTAL DISORDERS OF READING – DYSLEXIA In developmental dyslexia, children have a reading age which is lower than their chronological age, and the children have particular difficulties in reading and writing, both in terms of accuracy and fluency. The difficulties are out of proportion to their non-verbal IQ measures. Although children with dyslexia will learn to read and write, they will often show persistent problems, for example with spelling. They will also show ‘phonological’ problems – for example, difficulties in segmenting heard words around the onset/rhyme distinction. Children and adults with dyslexia often have problems, for example, with swapping onsets and rhymes around to make spoonerisms, for example turning ‘windy day’ into ‘dindy way’. There are more possible accounts of dyslexia than can be done justice to in a book about dyslexia, let alone a section in a chapter on language disorders. There have been accounts based on visual-processing deficits, problems in general task learning, and auditory processing. One important factor is that ‘normal’ reading and writing development involves use of ‘phonological’ information, which typically refers to aspects of the sound structure of words rather than to their phonetic construction (Snowling,

11.7 Developmental disorders of language 1998). Thus the ability to learn to read is predicted by children’s ability to tell that two words have the same onset, or rhyme; this ability is predictive of reading/writing development, even if a child is learning to read a nonalphabetic script, such a written Chinese. Once children have learnt to read, they can break words down into phonemes, such that cat becomes C, A and T; this skill is a consequence of learning to read, however, and it is important in dyslexia research to identify problems which are a result of the dyslexia, rather than due to the child’s slower acquisition of reading and reading-related skills. The causes of these phonological deficits, which seem to hinder reading and writing in dyslexia, are still unknown, and there is a lot of interest in the possible role of auditory-processing deficits (Goswami, 2010) or deficits in the ways that children can access motor representations when performing ‘phonological’ tasks (Snowling, 1998).

DEVELOPMENTAL DISORDERS OF SPEECH PRODUCTION In terms of speech production, one of the most difficult developmental disorders is a developmental dysfluency, commonly known as stammering or stuttering (Wingate, 1976). In stuttering, children have tremendous difficulties in speaking aloud, and can get stuck (known as ‘blocking’) on the start of a word, or repeating the start of a word, or prolong (stretch out) their speech sounds. Around 80 per cent of children with a developmental dysfluency will develop fluent speech production by the end of puberty; however, 20 per cent of children have a persistent problem which persists into adulthood. Despite the severity of the disorder – humans tend to strongly value fluency in verbal behaviour, and can be very intolerant of speakers whose speech is slow or hesitant, and the social anxiety associated with this knowledge can make a stammer much worse – we still do not have a unifying theory about stammering, nor any predictive information about why some people’s stammers resolve while others are left with a life-long difficulty. Strikingly, a variety of different ways of altering someone’s auditory environment and what their speech sounds like can improve developmental dysfluencies. Thus altering the acoustic consequences of spoken language by changing the pitch of someone’s voice, or playing their speech back with a noticeable delay typically improves people’s stuttering: several of these techniques have been incorporated into devices (e.g. built into phones, or as apps) that people who stutter can use to help them communicate. Strikingly, these techniques (e.g. introducing a delay) adversely affects the speech of fluent talkers, and can lead to them producing very dysfluent speech. Whispering also commonly improves stuttering. Altering the acoustic environment – for example, by putting people in noisy rooms, or getting them to talk in concert with someone else – also improves fluency. All of these improvements are transient, meaning that the improvements do not persist once the devices have been turned off (Howell, 2011). However, the fact that they all improve speech fluency suggests strongly that stuttering may not be a straightforward disorder of speech motor

367

368

Chapter 11 | Disorders of language control, but may reflect a disordered processing of the dynamic perceptual control and guidance of speech production.

DISORDERS OF LANGUAGE USE IN AUTISM Autism is a term covering a spectrum of developmental disorders, which can vary in severity from people who have profound learning disabilities through to people who can lead independent lives, but who may still experience considerable difficulties in their social interactions (Happé, 1999). Over the spectrum of autistic issues, there is considerable heterogeneity, with two main features, which seem to separately contribute to the profile. The first difference is one of perceptual processing, and can be crudely characterised as a problem of ‘seeing the wood for the trees’: people on the autistic spectrum can show an enhanced ability to focus on finer perceptual details, across sensory modalities. This means that they can do better at detecting embedded figures that a neurotypical control group, but it comes at the cost of poorer sensitivity to higherorder structure. Thus in speech perception and auditory processing, people with autism can be better at detecting pitch changes than a control group, but worse at understanding profiles of pitch that lead to prosody differences. The second common difference is one of perspective taking. It can be very hard for someone on the autistic spectrum to understand that someone else can know or believe something other than what they themselves know; this has been called a problem with ‘theory of mind’. In practical terms, one of the most problematic aspects of difficulties in seeing the world from someone else’s perspective is in social interactions, especially in conversation, where (as we saw in Chapter 10) people rarely say absolutely everything they mean, and trust that those they are talking to will understand the context in which their words are said. If, as we’re unpacking the shopping and I’m about to start cooking lunch in something of a hurry, I say to my sister ‘there were eggs on the kitchen table’, then she is likely to interpret this as a request to know where the eggs are now, as only she and I are putting the shopping away. If she does not use context however, she might well reply ‘yes I know there were’ or ‘why are you telling me that?’ as without the use of context, it is a mystifying comment to make. While language acquisition can be delayed for people who have autistic symptoms, it has been argued that the lasting problem is not one of a language deficit per se, and more of a problem in the use of language. This can make social interactions even harder for people who are already experiencing considerable problems.

SUMMARY t
When we discuss language in the brain, we are discussing a wide range of representations and processes across perceptual, motoric, conceptual and syntactic levels. Language use incorporates both linguistic and non-linguistic processes, and it can be disturbed and disrupted in a wide variety of ways.

11.7 Developmental disorders of language

t
Despite Henry Head’s distaste for ‘diagram-makers’ (Head, 1926), considerable developments have been made by using cognitive models to reflect both on the different ways that acquired brain damage can affect language, and also how language is processed in the normal, healthy brain. t
Many aspects of the Kussmaul–Wernicke–Lichtheim model have subsequently been supported by functional-imaging studies, including a dissociation between speech motor control, speech perception centres, and the wider semantic-conceptual system. t
In the distinction between anterior cortical temporal lobe areas which support the processing of intelligibility in speech, and posterior cortical temporal lobe areas which are important in repetition, there is some support for the concept that the phonological input lexicon may be distinct from the phonological output lexicon. t
When the field is extended to include reading, we can see both reading-specific profiles (e.g. in the visual work form area) and activations common to reading and speech comprehension (e.g. in the anterior temporal lobe, STS and fusiform gyrus). t
Finally, developmental disorders of language reveal the potential impact of phonological deficits on reading development, and separable contributions of syntactic deficits and verbal working memory on specific language impairments. We can see a potential role for auditory processing in stuttering, and a problem of the social use of language in autism.

FURTHER READING t
Harley, T. A. (2007). The Psychology of Language: From Data to Theory. Hove: Psychology Press. t
Ward, J. (2006). The Student’s Guide to Cognitive Neuroscience. Hove: Psychology Press. t
Hulme, C. and Snowling, M. J. (2009). Developmental Disorders of Language Learning and Cognition. Chichester: Wiley-Blackwell. 

369

Chapter 12

Contents 12.1 Introduction

371

12.2 Mood and attention

372

12.3 Mood and memory

374

12.4 Judgement and decision-making: mood effects

380

12.5 Judgement and decision-making: cognitive neuroscience

391

12.6 Reasoning

395

Summary

396

Further reading

397

Cognition and emotion Michael Eysenck

12.1 INTRODUCTION As the previous chapters in this book have revealed, psychologists have made considerable progress in understanding human cognition. In spite of that success, there is still some scepticism concerning the value of cognitive psychology. More specifically, it is sometimes doubted whether most research in cognitive psychology possesses ecological validity, which refers to the extent to which experimental findings are applicable in the real world. How does cognitive psychology research lack ecological validity? One of the most important ways relates to participants’ mood state when taking part in experiments. Experimenters typically try to ensure that participants are in a fairly neutral mood state. Note, however, that there are several exceptions. For example, participants in studies on eyewitness testimony are often exposed to emotionally threatening scenes that generate fear and anxiety (see Chapter 6). The neutral mood state of most laboratory participants contrasts very much with everyday life with its pleasures, frustrations and disappointments. In the real world, thinking, problem-solving and decision-making often occur when we are happy, anxious, sad or angry. This difference between the laboratory and everyday life is important, because it is indisputable that our cognitive processes and performance are influenced by our current mood state. Why have numerous researchers focused so strongly on human cognition in unemotional states? Part of the answer is that cognitive psychology for many years was much influenced by the computer analogy – the notion that information processing in humans resembles that in computers. Since it appears improbable that computers have mood states, use of the computer analogy led to limited interest in the effects of emotion on cognition. There is accumulating evidence that mood states influence important aspects of everyday life. Consider, for example, a study by Pecher et al. (2009) on the effects of music on car driving in a simulator. Drivers listening to sad music found it as easy as those listening to neutral music to keep the car in its lane, but there was a slight reduction in speed. In contrast, drivers found happy music to be distracting. It

12 Key Term Ecological validity The extent to which findings in psychology (especially those obtained in the laboratory) generalise to the real world.

372

Chapter 12 | Cognition and emotion reduced drivers’ ability to keep the car in lane and there was an 8 mph decrease in speed compared with the neutral music condition. The good news is that (rather late in the day!) there has recently been a substantial increase in research on emotion and cognition. This research has focused on the effects of mood state on cognitive processes such as perception, attention, interpretation, learning, memory, judgement, decision- making and reasoning. As we will see, positive mood states and negative mood states as diverse as anxiety, sadness and anger typically influence all of these cognitive processes. As indicated above, most of the research in this area has focused on mood states. There is a distinction between mood and emotion. In general terms, mood states are typically fairly long-lasting and lacking in intensity. In contrast, emotional states are usually fairly short-lasting but intense. Note, however, that there is substantial overlap between mood and emotions, and the distinction is often somewhat arbitrary. The emphasis in research has been on mood states because they are easier to manipulate and the induction of mild mood states poses fewer ethical issues than the induction of intense emotions (especially negative ones).

MANIPULATING MOOD STATES In much of the research on cognition and emotion, researchers have used various techniques to manipulate the mood states of their participants. One of the most effective techniques involves having participants write about personal events that created intense emotion in their lives. For example, Young et al. (2011) used this technique to create angry or sad mood states. Griskevicius et al. (2010) told their participants to write about a situation ‘when another person really took care of you and made you feel better’ to create feelings of attachment love. Another technique is to use music to manipulate mood state, as was done in the study by Pecher et al. (2009) discussed above. A further technique was devised by Velten (1968). It involves participants reading emotional sentences that are intended to produce progressively more intense positive or negative feelings. This technique changes individuals’ mood states. However, it often produces changes in various moods in addition to the one intended (Polivy, 1981).

12.2 MOOD AND ATTENTION Key Term Easterbrook’s hypothesis The notion that high levels of arousal or anxiety cause a narrowing of attention.

In this section, we will be mostly concerned with the effects of mood state on attention. Do various mood states lead to a narrowing or a broadening of attention? Answering this question is of relevance to an understanding of mood effects on memory, because what we remember is strongly influenced by what we attend to at the time of learning.

ATTENTIONAL NARROWING One of the first systematic attempts to understand emotional effects on attention and performance was put forward by Easterbrook (1959). According to Easterbrook’s hypothesis, the range of cues (i.e.

12.2 Mood and attention the environmental features receiving attention) reduces as arousal or anxiety increases, which ‘will reduce the proportion of irrelevant cues employed, and so improve performance … further reduction in the number of cues employed can only affected relevant cues, and proficiency will fall’ (Easterbrook, 1959: 193). In essence, Easterbrook was arguing that anxiety or arousal creates what is popularly known as ‘tunnel vision’ (excessive focusing of attention). Most of the research has supported the hypothesis by finding that anxiety leads to a narrowing of attention (Eysenck, 1992). In other words, anxiety reduces the spatial area to which attention is paid. Why does anxiety cause attention to become narrower? According to Gable and Harmon-Jones (2010), anxiety is a negative emotional state high in motivational intensity. Individuals become anxious when in threatening situations, and so they are motivated to attend (and respond) to the source of the threat. What are the effects on breadth of attention of the negative emotional state of sadness? Gable and Harmon-Jones (2010) argued that we become sad when we discover that some goal is unattainable. Sad individuals need to be open to new possibilities and this might cause broadened attention. As predicted, they found that sadness was associated with attentional broadening rather than narrowing. Thus, the presence or absence of high motivational intensity is important in determining whether there is attentional narrowing.

ATTENTION AND MEMORY Attentional narrowing helps to determine the effects of mood on memory. Levine and Edelstein (2009) argued that a slightly modified version of Easterbrook’s hypothesis could account for many of the effects of anxiety or stress on long-term memory. According to them, emotion enhances our memory for information central to our current goals but impairs it for peripheral or unimportant information. There is reasonable support for the above hypothesis. For example, Cavenett and Nixon (2006) studied the effects on memory of anxiety created by having skydivers learn words while on a plane just before they jumped out of it. In the control condition, the skydivers did their learning on the ground. When tested on the ground, the total number of words recalled was similar in the two conditions. However, the balance of what was recalled differed. Those skydivers who had learned under stressful conditions recognised more skydiving-relevant words than those in the control group. However, they recognised fewer words irrelevant to skydiving. These findings suggest that anxiety increases the focus on relevant stimuli at the expense of non-relevant ones. Easterbrook’s hypothesis is of some relevance to eyewitness testimony (Chapter 6). Consider what happens when an eyewitness is confronted by someone with a gun or other weapon. Loftus et al. (1987) found that memory for details was poor when eyewitnesses watched a person pointing a gun at a cashier and receiving some money. Memory for details of the same scene was better in the unemotional situation

373

374

Chapter 12 | Cognition and emotion

Key Term Weapon focus The finding that eyewitnesses pay so much attention to some crucial aspect of the situation (e.g. a weapon) that they ignore other details.

in which the person handed a cheque to the cashier. Loftus et al. used the term weapon focus to refer to the way in which a weapon attracts attention and thus reduces attention to (and memory of) peripheral details. Talarico et al. (2009) asked their participants to recall eight emotional autobiographical memories. These memories covered four positive emotions (happy; calm; in love; positive surprise) and four negative ones (negative surprise; angry; sad; afraid). There was poor memory for peripheral details with memories of anger, fear and negative surprise, as might be expected on Easterbrook’s hypothesis (Figure 12.1). In contrast, sad memories were associated with reasonably good recall of peripheral details, which is consistent with the findings of Gable and Harmon-Jones (2010) discussed earlier. What did Talarico et al. (2009) find with respect to the recall of positive autobiographical memories? There was good recall of peripheral details for all categories of positive memories. This suggests that individuals in a positive mood state show a broadening of attention.

12.3 MOOD AND MEMORY Learning and memory are affected in several ways by mood. Two main approaches can be taken to assess these effects. First, researchers can manipulate participants’ mood state at learning and/or retrieval. Second, researchers can consider the effects on memory of intensely emotional events in the world at large or in an individual’s personal life. We will be considering both approaches in what follows. After that, we will focus on the amygdala, a part of the brain that plays a central role in emotional processing.

0.50

Positive emotions

Negative emotions

Figure 12.1 Mean proportion of total details of autobiographical memories that were rated as peripheral for four positive and four negative emotions. The emotions are ordered on the basis of the proportion of peripheral details. Source: Talarico et al. (2009).

Peripheral/total details

0.45

0.40

0.35

0.30

0.25 Positive surprise

Calm

Happy

In love

Sad

Negative surprise

Afraid

Angry

12.3 Mood and memory

375

MOOD MANIPULATIONS AND MEMORY Think of times in which you have experienced a negative mood state perhaps because something has just gone wrong in your life. What kinds of memories spring to mind at such times? Most people find themselves recalling far more negative or unpleasant than pleasant memories. Conversely, when we are in a good mood, we naturally find ourselves recalling happy personal memories. These are examples of mood-congruent memory – memory is better when the learner’s (or rememberer’s) mood state matches the emotional content of the material. Many studies have obtained evidence of mood congruity effects on memory. Some of this research has focused on autobiographical memories. Miranda and Kihlstrom (2005) asked adult participants to recall autobiographical memories from childhood and adulthood when presented with pleasant, unpleasant and neutral cues. Music was used to produce a happy, sad or neutral mood. There was good evidence of mood congruity – retrieval of sad memories was facilitated by a sad mood and retrieval of happy memories was enhanced by a happy mood. Holland and Kensinger (2010) reviewed the literature on mood and autobiographical memory. They concluded that there is a reliable mood-congruent memory effect when people are in a positive mood. However, mood-congruent memory is found less reliably when people are in a negative mood. That is also the case in studies of mood congruity with positive and negative emotional material not of an autobiographical nature (Rusting and DeHart, 2000). Why is mood-congruent memory relatively elusive with negative mood? Negative mood states are unpleasant and so individuals in such a mood state are motivated to change their mood into a more positive one. Any reduction in negative mood state is likely to reduce the accessibility of negative memories. Support for the above explanation was reported by Rusting and DeHart (2000). In their study, participants wrote sentences about negative, positive and neutral words. After that, the participants were put into a negative mood state by thinking about experiencing distressing events. Next the participants were assigned to three conditions. In one condition, they were told to continue focusing on negative thoughts, whereas in another condition they engaged in positive reappraisal of the distressing events (e.g. ‘List some good things that could happen as a result of any of the negative events in the stories’). Finally, there was an unexpected test of free recall for all the words presented initially. What did Rusting and DeHart (2000) find? The typical moodcongruency effect was found in the continued focus condition, whereas participants in the positive reappraisal condition showed mood incongruity (i.e. better recall of positive than of negative words). These effects were much stronger among participants who had indicated previously that they were generally successful at regulating negative mood states. These findings suggest that the reason that moodcongruency effects are hard to find with negative mood states is because people strive to improve their mood.

Key Term Mood-congruent memory The finding that learning and retrieval are better when the learner’s (or rememberer’s) mood state is the same as (or congruent with) the affective value of the to-beremembered material.

376

Chapter 12 | Cognition and emotion

Key Term Mood-statedependent memory The finding that memory performance is better when the individual’s mood state is the same at learning and retrieval than when it differs.

There are two possible explanations of most mood-congruity effects (Fiedler et al., 2001). First, they may be due to a genuine memorial advantage for mood-congruent material. Second, they may be due to a response bias with individuals being more willing to report memories matching their current mood state even if they are not genuine ones. Fiedler et al. obtained no evidence that mood-congruity effects are due to response bias. In other words, incorrect memories were not more likely when they matched participants’ current mood state than when they did not. As a result, Fiedler et al. (2001) concluded that mood congruity is a genuine memory effect. Another effect of mood on memory is mood-state-dependent memory. It occurs when memory is better when the mood state at retrieval matches that at learning than when the two mood states are different. There is some similarity between the notion of mood-state-dependent memory and that of mood-congruent memory. However, one important difference is that mood-state-dependent memory is not necessarily linked to the emotional content of the to-be-remembered information, whereas there is such a link with mood-congruent memory. Ucros (1989) found in a review of forty studies that there was moderate support for the phenomenon of mood-state-dependent memory. The effects were greater when participants were in a positive mood than a negative one, which resembles the findings for mood-congruent memory. The explanation is the same – individuals in a negative mood state are motivated to change it in a positive direction. Eich (1995) argued that mood-state-dependent effects on memory can be explained in terms of a ‘do-it-yourself’ principle. In essence, such effects are much more likely to be found when participants have to generate crucial information (i.e. the to-be-remembered material or the retrieval cues) for themselves (e.g. in free recall) rather than having it explicitly presented (e.g. in recognition memory). We can see the value of Eich’s do-it-yourself principle by considering the findings of a study reported by Pamela Kenealy (1997). Participants learned instructions concerning a given map route in happy or sad conditions and then had their memory tested the following day in happy or sad conditions. Two memory tests were used: (1) free recall, in which participants had to generate their own retrieval cues; and (2) cued recall, in which the visual outline of the map was present to facilitate retrieval. What did Kenealy (1997) find? The results are shown in Figure 12.2. There was a strong mood-state-dependent effect in free recall. When retrieval cues were presented (i.e. in cued recall), there was no evidence of mood-state-dependent memory. What causes mood-state-dependent memory? Information about the to-be-remembered material and contextual information (often including information about mood state) are encoded at the time of learning. At the time of retrieval, various kinds of information (including information about current mood state) are available. According to the encoding specificity principle (Tulving, 1979; see Chapter 6), memory is better when there is much overlap of the information available at learning and

100 90 80 70 60 Sad

Happy

Mood at learning (a) Sad at recall

Learned items recalled (%)

Learned items recalled (%)

12.3 Mood and memory

377

100 90 80 70 60 Happy

Sad

Mood at learning (b) Happy at recall

Figure 12.2 (a) Free recall and (b) cued recall as a function of mood state (happy or sad) at learning and at retrieval. (Based on data in Kenealy, 1997.) Source: Eysenck and Keane (2010).

at test than when there is little overlap. This overlap is greater when participants are in the same mood state at learning and at test than when the mood state changes.

FLASHBULB MEMORIES How good is your memory for dramatic world events (e.g. 9/11)? Most people believe they have very good memory for such events. Interest in flashbulb memories (vivid and detailed memories of dramatic events) goes back to Brown and Kulik (1977). According to them, dramatic events that are surprising and have genuine consequences for the individual trigger a special neural mechanism. This mechanism ‘prints’ the details of such events more or less permanently in long-term memory. There is some evidence for strong and long-lasting flashbulb memories (Eysenck, 2012). However, such memories are often surprisingly inaccurate. Talarico and Rubin (2009) reviewed research on flashbulb memories, and they concluded that there is nothing special about flashbulb memories in terms of the underlying processes. Flashbulb memories seem especially vivid because they typically refer to distinctive events and so suffer little interference from other memories. Flashbulb memories are discussed in detail in Chapter 6.

RECOVERED MEMORIES Most of the evidence suggests that memories formed in strong emotional states are well remembered. However, the bearded Austrian psychologist Sigmund Freud argued that precisely the opposite is sometimes the case. More specifically, he claimed that memories of traumatic events (e.g. childhood sexual abuse) often cannot be recalled because they are subject to motivated forgetting and are relegated to the unconscious mind. Freud used the term repression to refer to this phenomenon.

Key Term Flashbulb memories Apparently vivid detailed memories of dramatic and significant events (e.g. 9/11). Repression Motivated forgetting of traumatic or other very threatening events (e.g. childhood abuse).

378

Chapter 12 | Cognition and emotion

Key Term Recovered memories Childhood traumatic or threatening memories that are remembered many years after the relevant events or experiences.

How do we know that people have repressed memories if they are unable to recall them? What sometimes happens is that traumatic memories that had been forgotten for many years are suddenly remembered in adult life. Freud found that these so-called recovered memories were often recalled in the course of therapy. The notion of recovered memories has proved very controversial. Many experts (e.g. Davis and Loftus, 2007) argue that most recovered memories are actually false memories, meaning they refer to events that did not actually happen. As you can imagine, this is an area in which it is extremely difficult to obtain convincing evidence. One reason is that there are rarely independent witnesses of traumatic events such as childhood sexual abuse. It is probable that some recovered memories are genuine, whereas others are false. How can we decide which memories belong in each category? An important clue was provided by Lief and Feltowicz (1995) in a study on adult patients who admitted they had reported false memories. In 80 per cent of the cases, their therapists had suggested to them that they had been the victims of childhood sexual abuse. This happened because many therapists (especially psychoanalysts influenced by Freudian theory) believe strongly in the existence of recovered memories. Geraerts et al. (2007) explored the genuineness of recovered memories in a study on three adult groups who had suffered childhood sexual abuse. One group consisted of those whose recovered memories had been recalled initially inside therapy (suggestive therapy group). A second group consisted of those whose recovered memories had been recalled initially outside therapy (spontaneous recovery group). The third group consisted of those who had had continuous memories of abuse from childhood onwards (continuous memory group). Geraerts et al. (2007) obtained an approximate measure of the genuineness of each group’s memories by finding out how many had corroborating evidence (e.g. the person responsible had confessed). Such corroborating evidence was present for 45 per cent of the continuous memory group and 37 per cent of the outside-therapy group, but for 0 per cent of the inside-therapy group. These findings suggest that recovered memories recalled inside therapy are often false memories. In contrast, most recovered memories recalled spontaneously outside therapy are probably genuine (see Geraerts, 2012, for a review). How can we explain spontaneous recovered memories produced outside therapy? According to Freud, what happens here is the return of repressed traumatic memories. In fact, that is very unlikely to be the correct explanation. Clancy and McNally (2005/06) found that the great majority of adults reporting recovered memories described them as confusing or uncomfortable. Indeed, only 8 per cent described them as traumatic. An alternative (and much simpler) explanation is more likely. Many spontaneously recovered memories are recalled because of the presence of relevant retrieval cues. Clancy and McNally (2005/06)

12.3 Mood and memory

379

obtained support for this explanation. Examples of relevant retrieval cues included returning to the location at which the abuse took place or seeing a movie about childhood sexual abuse. In sum, there is very little support for Freud’s repression account (McNally and Geraerts, 2009). Many recovered memories (especially those recalled within therapy) are false memories. Of those recalled spontaneously outside therapy, very few possess the traumatic quality emphasised by Freud. Most spontaneous recovered memories can be explained by simple mechanisms such as the presence of powerful retrieval cues.

AMYGDALA The effects of emotion on long-term memory depend on several different regions of the brain. However, the brain area most involved is the amygdala. The amygdala is buried in the front part of the temporal lobe (Figure 12.3), and is associated with several emotions (especially fear). Note that the amygdala doesn’t operate in isolation. A crucial reason for its importance is that it acts as a hub with numerous connections to other brain regions including 90 per cent of all cortical areas (Sander, 2009). There is plentiful evidence that the amygdala is much involved in our processing of emotional stimuli. For example, Suslow et al. (2010) presented pictures of happy and sad faces so they couldn’t be perceived at the conscious level. In spite of that, there was activation of the amygdala. Patients suffering from major depression had a greater amygdala response to sad faces than to happy ones, whereas healthy controls showed the opposite pattern. Thus, both groups of participants showed greater amygdala activation to faces that matched their mood state. How can we show that the amygdala plays an important role in determining long-term memory for emotional material? One way is by assessing brain activity during the learning of such material. The prediction is that the probability of emotional items being remembered will be greater when they are associated with high levels of amygdala activation at the time of learning. Murty et al. (2010) conducted a meta-analysis (a form of statistical analysis based Figure 12.3 Image of the amygdala, a structure that forms part of the on combining the findings limbic system and that is activated in many emotional states. from numerous studies). They Source: Ward (2010).

380

Chapter 12 | Cognition and emotion

Key Term Meta-analysis A form of statistical analysis based on combining all the findings in a specific area to obtain an overall picture. Urbach–Wiethe disease A disease in which the amygdala and adjacent areas are destroyed; it leads to the impairment of emotional processing and memory for emotional material.

obtained reasonable support for the above prediction. What they actually found was that good long-term memory for emotional material was associated with greater activation during learning in a network of brain regions including the amygdala and parts of the temporal lobe involved in memory. Other research suggests that the effects of being in an emotional state at the time of learning are especially great on subjective vividness. Kensinger et al. (2011) assessed amygdala activity while participants studied emotional and neutral objects. Amygdala activity at learning predicted the vividness of subsequent memory for the objects presented but did not predict the number of details recalled.

URBACH–WIETHE DISEASE An alternative way of assessing the role played by the amygdala in emotional learning and memory involves the study of patients with Urbach–Wiethe disease. This is a disease in which the amygdala and adjacent areas are destroyed and there is a reduction in the intensity of emotional experience. Cahill et al. (1995) studied BP, a patient suffering from Urbach– Wiethe disease. He was told a story, in the middle of which was a very emotional event (a boy is severely injured after being involved in a traffic accident). Healthy controls showed much better recall of this emotional event than of the preceding emotionally neutral part of the story one week after learning. In contrast, BP recalled the emotional event less well than the preceding part of the story. The amygdala is involved in memory for positive information as well as negative information. Siebert et al. (2003) compared long-term memory for positive, negative and neutral pictures in healthy controls and in ten Urbach–Wiethe patients. The patients had poorer recognition memory than the controls for all picture categories, but their memory impairment was greatest for positive pictures and least for neutral ones.

SUMMARY AND CONCLUSIONS In sum, similar findings have been reported in studies on patients with Urbach–Wiethe disease and on healthy individuals in brain-imaging studies. In both cases, there is much evidence that the amygdala plays an important role in enhanced memory for emotional information. This happens in part because the amygdala has connections to brain regions (e.g. hippocampus; prefrontal cortex) strongly involved in memory processes (LaBar and Cabeza, 2006).

12.4 JUDGEMENT AND DECISIONMAKING: MOOD EFFECTS Our everyday lives are full of decisions of one sort or another. Most of these decisions are trivial (e.g. which programme will I watch on

12.4 Judgement and decision-making: mood effects television?) but others are very important (e.g. do I want to become a psychologist?). The essence of decision-making is that it involves choosing among various options by expressing a preference for one option over all the others. Judgement plays an important role in decision-making. We make judgements about the likelihood of various events occurring and then judge how we would feel if each event were to occur. Of particular importance to decision-making is whether our judgements about the future are optimistic or pessimistic. For example, your decision whether to become a psychologist might well be influenced by how optimistic or pessimistic you are that there will be plenty of well-paid and interesting jobs available for psychologists in the future. This section focuses primarily on the effects of various mood states on judgement and decision-making. As we will see, mood states influence an individual’s attitude towards risk-taking and this in turn affects his/her decision. What effect do you think negative mood states have on judgement and risk-taking? Many people predict that individuals experiencing negative affect will tend to be pessimistic in their judgements and risk-averse (i.e. making safe and cautious decisions). In contrast, it seems likely that individuals in a positive mood state will be optimistic about the future and so will tend to take risks. Experimental findings often support these predictions. Intriguingly, however, many findings fail to adhere to prediction. Much of the research in this area has focused on the effects of any given mood state on performance or behaviour. For example, does a particular mood state enhance or impair the quality of decisionmaking? The emphasis here is on outcome. While it is necessary to assess outcome effects, it is also important to consider the effects of mood state on the cognitive strategies used. The emphasis here is on processes. The take-home message is that a full understanding of the effects of a given mood state on judgement and decision-making requires a consideration of the performance outcomes and of the underlying processes leading to those outcomes.

ANXIETY We will start by considering the negative mood state of anxiety. One reason for doing so is because the findings are generally reasonably clearcut and in line with the commonsensical predictions described above. Anxiety is associated with concerns and worries about future threats (Eysenck, 1997). For example, Eysenck et al. (2006) used scenarios referring to very negative events (e.g. serious illness). The event in question could be a past event, a future possible event, or an future probable event. The participants indicated that they would have experienced more anxiety with the future events (possible or probable) than with the past events) thus indicating the future orientation of anxiety (Figure 12.4). In contrast, participants reported more depression or sadness for past negative events than for future ones. Since anxiety involves worry about future threats, it is not surprising to find that it is associated with pessimistic judgements about the

381

Key Term Decision-making This involves making a selection from various options, often in the absence of full information. Judgement This involves an assessment of the likelihood of an event occurring on the basis of incomplete information; it often forms the initial process in decision-making.

382

Chapter 12 | Cognition and emotion

future to a greater extent than any other negative emotional state. Lerner et al. (2003) asked American participants 115 Depression very shortly after the terrorist attacks of 9/11 to focus on the aspects of those attacks 110 that made them afraid, angry or sad. The key finding was that those participants who 105 Anxiety focused on what made them afraid estimated the probability of future terrorist attacks 100 as greater than did those in the other two groups. Past Future Future Most people have what is uncertain probable known as an optimistic bias. Scenario type This bias involves exaggerating the likelihood of positive events happening to them in Figure 12.4 Mean anxiety and depression scores (max. = 140) as a the future but minimising the function of scenario type (past; future uncertain; future probable) likelihood of negative events (N = 120). (From Eysenck et al., 2006.) happening. This optimistic Source: Eysenck and Keane (2010). bias seems to occur automatically and is still found even when people are offered rewards for making accurate predictions (Lench and Ditto, 2008). Lench and Levine (2005) studied optimistic bias. College particiKey Term pants judged whether various positive and negative events were more Optimistic bias or less likely to happen to them than to the average college students. An individual’s Participants put into a fearful mood were less optimistic about future mistaken belief that events than were those who had been put into a happy or neutral he/she is more likely mood. Mean anxiety and depression scores

120

than most other people to experience positive events but less likely to experience negative events.

Decision-making We turn now to the effects of anxiety on decision-making. Anxiety is generally associated with impaired decision-making. For example, Starcke et al. (2008) found that anxious participants had worse performance than neutral controls on a decision-making task (Game of Dice Task) that requires the use of various executive processes. This research was extended by Starcke et al. (2011). They found that decision -making on the Game of Dice Task was worse when participants performed an additional task requiring executive processes at the same time. There are undoubtedly various reasons why anxiety impairs decision-making. However, one of the main reasons is because anxiety impairs the efficiency with which executive functions are used during the performance of complex cognitive tasks (Eysenck et al., 2007). We have seen that anxious individuals are generally pessimistic about the future and show impaired decision-making. In addition,

12.4 Judgement and decision-making: mood effects anxiety is typically associated with the avoidance of risky decisionmaking (see Blanchette and Richards, 2010, for a review). Maner et al. (2007) made use of a computer-based balloon task on which participants gained rewards for blowing up a balloon provided it did not burst. Anxious individuals were more risk-averse than non-anxious ones – they blew up the balloon less. Lorian and Grisham (2011) studied risk taking in patients suffering from various anxiety disorders. These patients (and healthy controls) completed the Domain-Specific Risk-Taking Scale. This scale consists of thirty items assessing an individual’s likelihood of engaging in various risky activities (e.g. ‘Betting a day’s income at the horse races’; ‘Engaging in unprotected sex’). Overall, patients with social phobia (extreme fear of social situations) and generalised anxiety disorder (chronic worry) had lower risk-taking scores than the control group. One of the most interesting studies was by Raghunathan and Pham (1999). Participants had to decide whether to accept job A (high salary + low job security) or job B (average salary + high job security). Participants in an anxious mood state were much less likely than those in a neutral state to choose the high-risk option (job A): 32 per cent versus 56 per cent, respectively. We have seen that anxiety or fear can make people cautious and risk-averse, which often impairs their decision-making. That suggests the interesting hypothesis that patients with damage to brain areas associated with emotional experience might actually perform better than healthy individuals on a gambling task. Shiv et al. (2005) tested the above hypothesis in a study involving three groups. One group had brain damage to emotion areas (amygdala, orbitofrontal cortex and insular or somatosensory cortex). The other groups consisted of patients with brain damage in areas unrelated to emotion and of healthy controls. Participants were all given $20 to start with. They had to decide on each of twenty rounds whether or not to invest $1. They lost the money if a coin came up heads but gained $1.50 if it came up tails. Thus, participants gained an average of 25 cents every time they invested, and so the optimal strategy is to invest every time. What did Shiv et al. (2005) find? As predicted, patients with brain damage in emotion regions outperformed the other two groups. The detailed findings are shown in Figure 12.5. As you can see, all groups were willing to invest when they had won on the previous round. However, the groups differed substantially in their investment behaviour if they had lost on the previous round. Patients with damage to emotion areas were far more likely than those in the other two groups to invest in those circumstances. The anxiety created by loss deters individuals from taking risks except in the case of brain-damaged patients who experience very little anxiety. In a similar study, De Martino et al. (2010) studied loss aversion in two women. Both of these women had suffered severe damage to the amygdala, which is of crucial importance in fear and other emotional states. The key finding was that neither of the women showed any

383

384

Chapter 12 | Cognition and emotion

evidence of loss aversion. As De Martino et al. concluded, it seems as if the amygdala 90 acts as a ‘cautionary brake’. It has been established 80 clearly that anxiety is associ70 ated with risk aversion. What is somewhat less clear is pre60 cisely why this is the case. However, we can identify two 50 major factors. First, anxious individuals are reluctant to 40 make risky decisions because 30 they are more pessimistic than non-anxious individuals 20 about the likely outcome. Second, anxiety is an aversive 10 mood state and so anxious individuals seek ways of reducing 0 Invested and lost Invested and won their level of anxiety. How can this be achieved? It is known Previous round that high levels of situational Patients with emotion-region damage Healthy controls uncertainty increase anxiety Patients with non-emotion-region damage (Frijda, 1986). Sarinopoulos et al. (2010) studied brain activity indicative of stress and Figure 12.5 Percentage of rounds in which patients with damage to anxiety in response to averemotion regions of the brain, patients with damage to other regions of the sive pictures. There was greater brain, and healthy controls decided to invest $1 having won or lost on the previous round. (Data from Shiv et al., 2005.) brain activity when participants were uncertain whether an averSource: Eysenck (2012). sive or neutral picture would be presented next. Reducing uncertainty by making low-risk decisions (e.g. choosing a job with high security) is an effective way of reducing anxiety. Percentage investing

100

SADNESS Sadness resembles anxiety in that both are negative mood states. However, there is an important difference. Sadness (which turns into depression when sufficiently intense) is associated with an absence of positive affect to a greater extent than anxiety (Clark and Watson, 1991). As a consequence, sad individuals experience the environment as being relatively unrewarding, and this may motivate them to obtain rewards even if risks are involved.

Decision-making Studies on the effects of sadness on judgement were reviewed by Waters (2008). Sad individuals regarded the likelihood of health hazards and adverse life events as greater than did happy or positive individuals. The notion that sad individuals may be motivated to reduce their sadness by obtaining rewards suggests they may be less averse to risk

12.4 Judgement and decision-making: mood effects than anxious individuals. That is, indeed, what is indicated by the limited evidence available. Earlier I discussed a study by Raghunathan and Pham (1999) in which participants had to choose between a high-risk and a low-risk job. Anxiety led participants to favour the low-risk job. In contrast, sadness caused participants to select the high-risk job – 78 per cent of sad participants did so compared with only 56 per cent of those in a neutral mood. This finding can be explained on the basis that sad participants were motivated to obtain the reward of high pay associated with the high-risk option. Some research has focused on the decision-making processes used by individuals in a sad mood. We can distinguish between two major types of processing. First, there is systematic or analytic processing which is relatively slow and consciously controlled. Second, there is heuristic processing which is relatively effortless and involves using heuristics (rules of thumb). The evidence suggests that sad individuals tend to use analytic processing (Andrews and Thomson, 2009). In a literature review, Schwarz (2000) concluded that being in a sad mood causes people to use a processing strategy in which much attention is paid to details. This is in essence analytic processing. De Vries et al. (2008) hypothesised that people are most satisfied with their decision-making when they have made use of their preferred processing strategy. They tested this idea by requiring participants to use heuristic/intuitive or analytic/deliberative processing when making a decision. As predicted, participants put into a sad mood by watching a clip from Schindler’s List were more satisfied with their decision following analytic/deliberative processing than when following heuristic/ intuitive processing. This study is discussed further later in the chapter.

ANGER It is important not to exaggerate the similarities among negative emotional states. That is especially the case with anger, which differs in several ways from other negative states such as anxiety and sadness. Even though anger is regarded as a negative emotional state, it can be a moderately positive emotion if the individual believes he/she can control the situation and dominate disliked others (Lerner and Tiedens, 2006). However, there are probably important cross-cultural differences here. For example, consider the Machiguenga Indians in the Peruvian Amazon. They are a very peaceful people who regard fear as preferable to anger and who avoid anger at all costs (Johnson et al., 1986). One example of how anger can lead to a positive emotional state is schadenfreude. This involves experiencing pleasure at the misfortune of disliked others. Hareli and Weiner (2002) found that schadenfreude is greater in those who are angry. Leach and Spears (2008) studied a fictitious competition between the participants’ own university and a more successful other university. The failure of the successful university created schadenfreude. Much of this schadenfreude occurred because of the participants’ anger based on the pain of their university’s inferiority.

385

386

Chapter 12 | Cognition and emotion Of course, anger is very often associated with negative affect as well as positive (Litvak et al., 2010). The events that cause anger are typically remembered as unpleasant. In addition, the consequences of anger (e.g. aggression; violence) can cause very negative emotional states. What are the effects of anger on judgement? Of interest, the effects are very different from those of anxiety or sadness. Waters (2008), in a review discussed earlier, found that anger was generally associated with fairly optimistic judgements about the likelihood of negative events. In other words, the perceived likelihood of negative events was low. In contrast, both anxiety and sadness were associated with pessimistic judgements. The optimism of angry individuals is surprising in view of the fact that individuals who are characteristically angry are more likely than other people to have cardiovascular problems and to be divorced (Lerner and Keltner, 2001). Why does anger differ from other negative emotional states in being associated with optimistic judgements? What is important is that anger (unlike anxiety or sadness) is associated with perceived control over others (Litvak et al., 2010). Angry individuals feel in control and thus able to determine their own destiny, which makes them optimistic about the future. In contrast, anxious and sad individuals have much less perceived control and feel themselves at the mercy of fate and of other people. As a result, they are pessimistic about the future.

Decision-making It is popularly assumed that anger greatly reduces our ability to think rationally and to make sensible decisions. In the words of the American philosopher Ralph Waldo Emerson, anger ‘blows out the light of reason’. As we will see, there is reasonable support for this point of view (see Litvak et al., 2010, for a review). One example of anger impairing decision-making comes in a study by Bright and Goodman-Delahunty (2006). The participants were mock jurors who had to decide on the guilt or innocence of a man who was alleged to have murdered his wife. Some of the jurors were made angry by seeing gruesome photographs taken of the murdered woman. The angry jurors were more than four times as likely as the non-angry ones to return a guilty verdict. Thus, their decision-making was greatly influenced by their anger. Another example was reported by Coleman (2010). He studied the sunk-cost effect, which is an increased tendency to invest resources in an uncertain project following previous failure with that project. Most people show this effect even though it would be preferable on average to accept the loss and invest elsewhere. In other words, the sunk-cost effect involves ‘throwing good money after bad.’ Coleman (2010) used a hypothetical problem in which students decided whether to do a course for which they had paid in advance or (at no extra financial cost) switch to a course offering a better chance of success. His key finding was that the sunk-cost effect was greater in angry participants than in those in a sad or neutral mood. Thus, anger increased the tendency for students to make a suboptimal decision.

12.4 Judgement and decision-making: mood effects Why does anger often impair the quality of decision-making? We can address that issue with reference to the distinction discussed earlier between systematic or analytic processing and heuristic processing which is based on heuristics (rules of thumb). According to Litvak et al. (2010), anger leads to increased use of heuristic processing and reduced used of analytic processing. Convincing evidence that anger increases the use of heuristic processing was reported by Small and Lerner (2008). Their participants were given a decision-making task. They had to decide how much welfare assistance should be received by a fictitious Patricia Smith, who was a 25-year-old divorced woman with three children. Angry participants awarded her less assistance than did participants put into a neutral or sad mood state. There was a further condition in which angry participants had to perform an additional cognitively demanding task at the same time as the decision-making task. This condition was designed to force participants to rely mostly on heuristic processing on the decision-making task. The key finding was that the addition of a second cognitively demanding task did not affect the amount of welfare assistance awarded by angry participants. The implication is that angry participants primarily used heuristic processing even in the absence of a secondary task. There is other evidence that anger causes judgements to be made on the basis of heuristic processing. Ask and Granhag (2007) induced anger in experienced police investigators by asking them to recall (and write about) an event they had encountered in their police work that had caused anger or sadness. After that, the police investigators read the summary of a criminal case together with statements by two witnesses. Finally, they judged the witnesses on several measures (e.g. reliability; trustworthiness) and judged the probability of guilt. What did Ask and Granhag (2007) find? The key finding was that angry participants engaged in more heuristic or superficial processing of the information about the case than did sad ones. For example, the judgements made by angry participants were less influenced than those of sad participants by the content of the witness statements.

POSITIVE MOOD There has been much interest in optimistic bias – the judgement that we are more likely than other people to experience positive events (e.g. a pleasant holiday) but less likely to experience negative events (e.g. divorce; serious illness). The obvious prediction is that individuals in a positive or good mood would exhibit a stronger optimistic bias than those in a neutral or negative mood. The evidence in favour of the above prediction is much weaker than might have been imagined. Drace et al. (2009) carried out several experiments on optimistic bias with mood state being manipulated by means of pictures and music. There was much general evidence for optimistic bias. More importantly, however, its extent was very similar across positive, negative and neutral mood states. The negative findings of Drace et al. (2009) contrast with previous research. In that research, it was often found that individuals in

387

388

Chapter 12 | Cognition and emotion a positive mood state perceived themselves as less likely to experience negative events than did sad individuals (Waters, 2008). How can we explain the difference? In many of the studies, the participants’ mood states were measured shortly before assessing comparative optimism. Thus, some participants may have guessed that the experimenter was interested in the relationship between mood and comparative judgements and altered their judgements accordingly. In contrast, Drace et al. designed their experiments so as to minimise the chance of such distortions occurring.

Decision-making What are the effects of positive mood states on decision-making? The first point to make is that such mood states are typically associated with a risk-averse approach to decision-making (Blanchette and Richards, 2010). For example, Mustanski (2007) carried out a diary study on men who have sex with other men. The prevalence of HIV risk behaviours was significantly less among men who experienced high levels of positive affect. Cahir and Thomas (2010) studied decision-making involving betting on imaginary horse races. Participants in a positive mood made less risky decisions than those who were in a neutral mood. Why does being in a positive mood cause people to become riskaverse? The most likely reason is that someone who is happy is motivated to maintain that positive state and so is disinclined to take chances. However, it could be argued that this interpretation is rather post hoc. Suppose it had been found that individuals in a positive mood are less risk-averse. It could plausibly be argued that individuals in a positive mood believe themselves largely immune from danger and so are inclined to take risks (anonymous reviewer). Much research on mood and decision-making has made use of the distinction between analytic or deliberate processing and heuristic or effortless processing. It has generally been found that being in a positive mood causes people to make more use of heuristic processing and less of analytic processing (see Griskevicius et al., 2010, for a review). De Vries et al. (2008) argued that people who use their preferred processing strategy are more content with the decisions they make that those who use a non-preferred strategy. We saw earlier that that was the case for participants put into a sad mood – they were more satisfied with their decision when required to use analytic/deliberative processing than when required to use heuristic/intuitive processing. In the same study, other participants were put into a happy mood by watching a video clip from The Muppet Show, whereas others were put into a sad mood by watching a video clip from the film Schindler’s List. The findings obtained by de Vries et al. (2008) supported their hypothesis (Figure 12.6). Happy participants were more satisfied with their decision following heuristic/intuitive processing than when following analytic/deliberative processing. The findings for sad participants were precisely the opposite. Thus, people are most content with

12.4 Judgement and decision-making: mood effects

389

Subjective value (euro)

their decisions when there is 14 a fit between their mood and the decision strategy they 13 have used. You may have been won12 dering (or maybe not!) about a strange difference 11 between research on negative and positive mood states. 10 Researchers in the former 9 area have distinguished among three different nega8 tive mood states (e.g. anxiety; sadness; anger). In contrast, 7 most researchers in the latter area have considered only 6 a single positive mood state. Intuitive Deliberative decision decision This makes sense only if all types of positive affect have Decision mode comparable effects on cogniHappy mood Sad mood tive processing. Griskevicius et al. (2010) compared the effects of sev- Figure 12.6 Subjective value associated with decision as a function of eral kinds of positive affect mood (happy vs. sad) and decision strategy (intuitive vs. deliberative). including attachment love, Source: de Vries et al. (2008). awe, contentment, anticipatory enthusiasm, amusement and nurturant love. The participants had to assess the persuasiveness of strong or weak arguments relating to the possible introduction of a new examination. The extent to which participants made use of heuristic processing (assessed by persuasiveness of weak arguments) varied across the different positive emotional states (Figure 12.7). Participants who experienced anticipatory enthusiasm, attachment love or

Attitude toward message

(+)

(−)

6.5 6.0 5.5 5.0 4.5 4.0 3.5 Neutral

Awe

Nurturant Amusement Anticipatory Attachment Contentment love enthusiasm love Positive emotion

Weak arguments

Strong arguments

Figure 12.7 Effects of six positive emotions on persuasiveness of arguments (weak vs. strong). Source: Griskevicius et al. (2010).

390

Chapter 12 | Cognition and emotion amusement all exhibited heuristic or shallow processing because they were persuaded even by weak arguments. However, awe and nurturant love were both associated with reduced heuristic processing compared with a neutral mood state. Thus, positive emotional states vary in their effects on cognitive processing. However, more research is needed to clarify why each positive state has the specific effects it does.

SUMMARY AND CONCLUSIONS The most important finding to emerge from research on the effects of mood state on judgement and decision-making is that each mood state is associated with its own pattern of effects (Figure 12.8). How can we make overall sense of the idiosyncratic pattern of effects associated with each mood state? There is as yet no satisfactory answer to that question. However, the starting point is to recognise that each mood state or emotion fulfils certain functions (Oatley and Johnson-Laird, 1987). It is probable that most moods or emotions fulfil more than one function, but we will focus mostly on the most important one in each case. What is the main function of anxiety? As discussed earlier, anxiety occurs in threatening situations in which there is uncertainty and unpredictability. It follows that an important function of anxiety is to reduce the aversive anxious state by increasing certainty and predictability. This can often be accomplished by minimising risk-taking and choosing safe options. Individuals become sad or depressed when they realise that some desired goal cannot be achieved. Sadness or depression leads the individual to abandon the goal that cannot be achieved and to engage in extensive thinking about which goal should replace it. Thus, the function of sadness or depression is to persuade individuals to rethink their goals and priorities. A theoretical approach along these lines was put forward by Andrews and Thomson (2009) in their analytic rumination hypothesis. They argued that depressed individuals have reduced motivation to engage in distracting activities and so focus on their symptoms and on what to do next (rumination). Such rumination involves analytic processing. This hypothesis helps to explain why sadness is the only mood state associated with analytic rather than heuristic processing. What is the main function of anger? Anger has the function of overcoming some obstacle to an important goal by direct (and often aggressive) action. This approach is most likely to be taken when the

Anxiety

Figure 12.8 Effects of mood states on judgment and decision-making.

Sadness

Anger

Positive mood

Judgement

Pessimistic

Pessimistic

Optimistic

Optimistic?

Attitude to risk

Risk averse

Risk taking

Risk taking

Risk averse

Processing

Inefficient

Analytic

Heuristic

Heuristic

12.5 Judgement and decision-making: cognitive neuroscience individual feels he/she has personal control and is thus optimistic that the goal can be achieved. This sense of personal control also persuades angry individuals to take risks to achieve what they want. What is the main function of positive moods or emotions? According to Oatley and Johnson-Laird (1987), the main function is to preserve or maintain the current mood. This leads happy individuals to engage in shallow or heuristic processing and to avoid taking risks that might endanger the positive mood state.

LIMITATIONS What are the main limitations of research on mood states and decision-making? Some of the main ones revolve around the issue of ecological validity or the extent to which the research findings generalise to real life. First, there is an important distinction between integral emotions and incidental emotions. Integral emotions are those of direct relevance to the situation and to the current task (e.g. decision-making). In contrast, incidental emotions are carried over from a previous situation and so are essentially irrelevant to the current task. Most of the research we have discussed has involved incidental emotions. For example, participants write about a personal event that made them very sad, anxious, angry or happy. After that, they perform a task that has nothing at all to do with that event. It is undoubtedly the case that some of our decision-making in real life is influenced by incidental emotions. However, it seems likely that we are more often influenced by integral emotions, but research so far has shed relatively light on what happens in such circumstances. Second, we have seen in studies of decision-making in laboratory conditions that various mood states are associated with shallow or heuristic processing. This may reflect in part the artificial nature of the research, since the decisions made by participants have no implications outside the laboratory situation. For example, individuals in real life deciding which job to take or which decision to make as jurors in a court case are unlikely to make rapid decisions based on heuristic processing. Third, there has been much emphasis in the literature on the distinction between heuristic or shallow processing and analytic or deliberate processing. This distinction is oversimplified (Keren and Schul, 2009). In practice, many cognitive processes cannot be categorised neatly as heuristic or analytic – they involve a combination of both types.

12.5 JUDGEMENT AND DECISIONMAKING: COGNITIVE NEUROSCIENCE We have just considered the ways in which various mood states influence judgement and decision-making. Cognitive neuroscience provides an alternative way of understanding the role played by emotional factors in judgement and decision-making.

391

392

Chapter 12 | Cognition and emotion Much of the research within the cognitive neuroscience approach has focused on very difficult moral problems of a particular type. Consider two related problems. In the trolley problem, you have to decide whether to divert a runaway trolley that threatens the lives of five people onto a side-track where it will kill only one person. In the footbridge problem, there is also a runaway trolley. This time, however, you have to decide whether to push a fat person over a bridge. This will cause the death of the person pushed but will stop the runaway trolley and prevent five deaths. About 90 per cent decide it is worth diverting the trolley in the trolley problem but only 10 per cent decide to push the person to push the person off the footbridge (Hauser, 2006). What is going on here? According to Greene (2007), the difference is that the footbridge problem triggers a strong emotional response. This causes us to disapprove of pushing the person to their death even though that would save five lives. More specifically, we respond strongly at an emotional level to the notion of causing direct harm to another person (which is not present in the trolley problem). Problems such as the footbridge problem are known as personal moral dilemmas. Greene et al. (2004) studied various personal moral dilemmas including the crying baby dilemma: Enemy soldiers have taken over your village. They have orders to kill all remaining civilians. You and some of your townspeople have sought refuge in the cellar of a large house. Outside, you hear the voices of soldiers who have come to search the house for valuables. Your baby begins to cry loudly. You cover his mouth to block the sound. If you remove your hand from his mouth, his crying will summon the attention of the soldiers who will kill you, your child, and the others hiding out in the cellar. To save yourself and the others, you must smother your child to death. Is it appropriate for you to smother your child in order to save yourself and the other townspeople? (Greene et al., 2004: 390) According to Greene et al. (2004), dilemmas such the crying baby dilemma are agonisingly difficult because of the conflicts they create. On the one hand, there is a very powerful emotional imperative not to smother one’s own baby (emotional argument). On the other hand, there is the powerful argument that more lives will be saved if you smother your child to death (cognitive argument). The problem is very hard because the emotional and cognitive factors are in direct conflict with each other. This explanation of decision-making with personal moral dilemmas is known as the dual-process theory. Some people attach more weight to the cognitive argument than to the emotional one. They generally make utilitarian judgements based on saving as many people as possible (e.g. smother your own child). Other people attach more weight to the emotional argument and make non-utilitarian judgements (e.g. do not smother your child).

12.5 Judgement and decision-making: cognitive neuroscience Suppose people were required to make moral judgements while at the same time performing a task that placed demands on cognitive processing. It would be predicted that this would increase the extent to which emotional considerations influenced moral decision-making and so lead to a reduction in utilitarian moral judgements. Greene (2007) discussed an unpublished study in which precisely this finding was obtained.

COGNITIVE NEUROSCIENCE RESEARCH

10

46

393

9

Figure 12.9 The dorsolateral prefrontal cortex is located approximately in Brodmann areas 9 and 46; the ventromedial prefrontal cortex is located approximately in Brodmann area 10.

How can cognitive neuroscience Source: Ward (2010). clarify what is happening in such decision-making? Two relevant brain regions are the dorsolateral prefrontal cortex (DLPFC) and the ventromedial prefrontal cortex (VMPFC, Figure 12.9). In approximate terms, the DLPFC is involved in cognitive control. In contrast, the VMPFC is (among other activities) important in the processing and generation of emotions. Suppose we consider activity within the DLPFC for those who make utilitarian (or ‘cognitive’) judgements and those who make non-utilitarian (or ‘emotional’) judgements on complex personal moral dilemmas (e.g. crying baby dilemma). We would expect the former individuals to exercise more cognitive control, and so they should show more activity in the DLPFC. Precisely that finding was reported by Greene et al. (2004) (Figure 12.10). Suppose we consider patients who have suffered damage to the VMPFC. Such patients have reduced emotional responsiveness and so should attach less weight than healthy controls to emo- Figure 12.10 Brain regions in the anterior dorsolateral tional arguments. Accordingly, we would prefrontal cortex that were activated more when utilitarian expect such patients to be more likely decisions were made than when non-utilitarian decisions than healthy controls to make utilitarian were made. or cognitive judgements with personal Source: Greene et al. (2004).

394

Chapter 12 | Cognition and emotion moral dilemmas. Koenigs et al. (2007) found that VMPFC-damaged patients made more than twice as many utilitarian judgements than healthy controls (45 per cent versus 20 per cent). This did not happen because brain damage impaired the patients’ ability to think effectively – there were no differences between them and the healthy controls on other judgement tasks. The limitation in the study by Koenigs et al. (2007) is that they did not provide any direct evidence that reduced emotional responsiveness in VMPFC patients was responsible for their tendency to make utilitarian judgements. This issue was addressed by Moretto et al. (2010). Healthy controls produced a strong emotional response (measured by skin conductance responses) before endorsing violations of personal morality. VMPFC patients approved more moral violations than controls. Of importance, they did not produce an emotional response before endorsing violations of personal morality. These findings support the view that the VMPFC is involved in assessing the emotional consequences of personal moral violations. The relevance of the VMPFC to emotional processing can be seen in individuals with antisocial personality disorder (popularly known as psychopaths). These individuals have an almost complete absence of empathy (emotional understanding of other people) in spite of having intact cognitive processing. Harenski et al. (2010) studied brain activity in criminal psychopaths and other imprisoned individuals in response to pictures showing moral violations. The non-psychopathic prisoners had greater activity in the VMPFC when viewing these pictures than other pictures. In contrast, there was comparable VMPFC in the psychopaths for all types of pictures, indicating that the pictures showing moral violations had no special emotional significance for them.

LIMITATIONS There is convincing evidence that personal moral dilemmas can cause substantial conflict between cognitive and emotional processes. This is as predicted by dual-process theory, as are the roles of DLPFC and VMPFC in influencing cognitive and emotional processing, respectively. In spite of the successes of dual-process theory, it is oversimplified in various ways, two of which we will consider here. First, the brain areas involved in decision-making with moral dilemmas are more widespread than is implied by the focus of the theory. Cognitive processing is associated with several brain areas in addition to the DLPFC and emotional processing involves areas additional to the VMPFC. Second, the account of cognitive processing with personal moral dilemmas is limited. It is assumed that the involvement of cognitive processing increases the tendency to prefer utilitarian judgemenss or decisions. In fact, matters are more complex than that as is discussed below. Broeders et al. (2011) argued that the moral rule that is most accessible to the cognitive system influences moral decisions. Participants were presented with the footbridge problem preceded by information

12.6 Reasoning

395

designed to lead them to focus on the moral rule, ‘Saving lives’ or the rule, ‘Do not kill.’ Participants for whom the rule ‘Saving lives’ was more accessible were significantly more in favour of pushing the person off the footbridge than those receiving the rule ‘Do not kill.’ Thus, focusing cognitive processes on certain moral rules can increase or decrease the tendency to make utilitarian judgements with personal moral dilemmas.

12.6 REASONING There has been a considerable amount of research on reasoning (see Chapter 8). Much of this research has focused on deductive reasoning, which allows us to draw conclusions that are certain provided that other statements are assumed to be true. One of the most popular deductive-reasoning tasks is syllogistic reasoning. Two premises or statements are presented (e.g. ‘All cats are obedient’; ‘Lulu is a cat’) followed by a conclusion (e.g. ‘Therefore, Lulu is obedient’). In this example, the conclusion must be valid if we accept the truth of the premises. It has generally been found that negative emotional states impair deductive reasoning (see Blanchette et al., 2007, for a review). Oaksford et al. (1996) used brief film clips to put participants into a negative or a positive mood state. Reasoning performance was impaired to a similar extent by both mood states. In spite of the general finding that emotional mood states have an adverse effect on reasoning performance, this is not invariably the case. Johnson-Laird et al. (2006) asked individuals with many or few depressive symptoms to list as many logical possibilities as they could when presented with various scenarios. The key finding was that high depressives produced many more valid possibilities than low depressives when the scenarios produced depressive feelings. Depressed individuals devote much more time than non-depressed ones in thinking about the causes of their depression, as a result of which they become expert at reasoning about depression.

WORKING MEMORY Why is reasoning performance impaired by various negative and positive emotional states? Before answering that question, we need to consider the cognitive processes involved in performing reasoning tasks. Of particular important is the central executive, which is a limitedcapacity, attention-like component of the working memory system (Baddeley, 2007; see also Chapter 5). There is much evidence (e.g. De Neys, 2006) that solving most reasoning problems requires extensive use of the central executive. Thus, one hypothesis as to why emotional states impair reasoning is because they deplete the resources of the central executive. There is reasonable support for the above hypothesis. Eysenck and colleagues (e.g. Eysenck and Calvo, 1992; Eysenck et al., 2007) have

Key Term Deductive reasoning An approach to reasoning in which conclusions can be judged valid or invalid given that certain statements or premises are assumed to be true.

396

Chapter 12 | Cognition and emotion argued that anxiety causes individuals to allocate some of their attention to task-irrelevant thoughts (e.g. ‘I am doing this task poorly’). Such thoughts pre-empt some of the resources of the central executive and this reduces performance on many cognitive tasks. In a study by Derakshan and Eysenck (1998), individuals with high and with low levels of anxiety performed a reasoning task at the same time as a second memory task that required (or did not require) use of central executive resources. The adverse effect of the second task involving the central executive was much greater among the highly anxious participants. This happened because the highly anxious individuals had fewer central executive resources available to perform the reasoning task. It is possible to explain the effects of sadness or depression on reasoning performance in a similar way. There is much evidence that depressed or sad individuals engage in much rumination (focusing on distress symptoms), which leads to impaired performance on several cognitive tasks (Gotlib and Joormann, 2010). In a study by Channon and Baker (1994), depressed individuals had poorer performance than non-depressed ones on syllogistic reasoning problems. Of most interest, the depressed participants found it hard to integrate information from the two premises, which is demanding of central executive resources. What about the effects of positive mood state on working memory? Martin and Kerns (2011) found evidence that positive mood state impaired the functioning of the central executive. In a study discussed above, Oaksford et al. (1996) found that positive mood impaired reasoning performance. In another experiment, they obtained a comparable impairment when participants had to perform a second task demanding of central executive resources at the same time as the reasoning task. These findings suggest that positive mood depletes central executive resources.

SUMMARY t
Anxiety leads to attentional narrowing, whereas a sad mood leads to attentional broadening. These effects of mood on attention partly explain why memory for peripheral information is greater in a sad mood than an anxious one. t
Mood-congruent memory is greater in positive moods than in negative ones because individuals in a negative mood are motivated to improve their mood state. t
There is more evidence of mood-state-dependent memory when people have to generate their own retrieval cues. t
Memories of childhood abuse initially recalled outside therapy are more likely to be genuine than those initially recalled inside therapy. Freud’s notion of repression is an unconvincing explanation of recovered memories.

12.6 Reasoning

t
Each of the three negative mood states (anxiety; sadness; anger) has an idiosyncratic pattern of effects on judgement and decision-making. These differences reflect the different functions fulfilled by each mood state. t
Angry and positive moods are associated with heuristic or shallow processing, whereas sad mood is associated with analytic processing. t
Angry, sad, anxious and positive moods all lead to impaired reasoning performance. The main reason is that all these mood states deplete the resources of the central executive. t
Personal moral dilemmas produce a serious conflict between emotional and cognitive considerations. The ventromedial prefrontal cortex is involved in emotional responsiveness and the dorsolateral prefrontal cortex is involved in cognitive processing of dilemmas.

FURTHER READING t
Blanchette, I. and Richards, A. (2010). The influence of affect on higher level cognition: A review of research on interpretation, judgment, decision making and reasoning. Cognition and Emotion, 24, 561–595. Isabelle Blanchette and Anne Richards provide a reasonably comprehensive account of the effects of several emotional states on human cognition. t
Eysenck, M. W. and Keane, M. T. (2010). Cognitive Psychology: A Student’s Handbook (6th edn). Hove: Psychology Press. Chapter 15 in this textbook covers the effects of cognitive processes on emotion as well as the effects of emotion on cognition. t
Fox, E. (2008). Emotion Science: Cognitive and Neuroscientific Approaches to Understanding Human Emotions. New York: Palgrave Macmillan. Elaine Fox discusses effects of emotion on cognition in a comprehensive way, especially in Chapters 6–8. t
Litvak, P. M., Lerner, J. S., Tiedens, L. Z. and Shonk, K. (2010). Fuel in the fire: How anger impacts judgment and decision-making. In M. Potegal, G. Stemmler and C. Spielberger, (eds) International Handbook of Anger: Constituent and Concomitant Biological, Psychological, and Social Processes (pp. 287–310). New York: Springer. This chapter provides a comprehensive overview of the unexpected effects of anger on cognition.

397

Glossary Active perception Perception as a function of interaction with the world. Affordances Represent the interaction of the individual with the environment. Objects afford the use to which the individual can put them. Agnosia The failure to recognise or interpret stimuli despite adequate sensory function. It is usually classified by sensory modality, so visual agnosia is the failure to recognise objects that are seen. Alexia/dyslexia Both refer to problems in reading written language. Alexia always refers to acquired difficulties in reading, while dyslexia is used to refer to developmental difficulties in reading. However some specific acquired reading problems – e.g. deep versus surface dyslexia – are used to refer to particular profiles of acquired reading problems. Alzheimer’s disease (AD) A degenerative brain disorder usually (but not always) afflicting the elderly, which first appears as an impairment of memory but later develops into a more general dementia. Amnesia A pathological impairment of memory function. Anterograde amnesia (AA) Impaired memory for events which have occurred since the onset of the disorder (contrasts with retrograde amnesia). Aphasia An acquired language disorder, which primarily affects the comprehension of

spoken language (a receptive aphasia), or the production of spoken language (expressive aphasia). In global aphasia, both speech production and perception are compromised. Articulatory suppression A task used to occupy the articulatory control process of the working memory, normally involving the repetition of a sound (such as ‘the’) which requires articulation but little processing. Attention conspicuity The interaction of aspects of a stimulus (such as colour, luminance, form) with aspects of an individual (such as attention, knowledge, preconceptions) that determine how likely a stimulus is to be consciously perceived. (See also sensory conspicuity.) Automatic processing Processing that does not demand attention. It is not capacity limited or resource limited, and is not available for conscious inspection (contrasts with controlled processing). Availability heuristic Making judgements on the basis of how available relevant examples are in our memory store. Base rate fallacy Ignoring information about the base rate in light of other information. Behaviourism An approach to psychology which constrains psychologists to the investigation of externally observable behaviour, and

rejects any consideration of inner mental processes. Binaural cues Cues that rely on comparing the input to both ears, as for example in judging sound direction. Binding problem The problem of how different properties of an item are correctly put together, or bound, into the correct combination. Blindsight The ability of some functionally blind patients to detect visual stimuli at an unconscious level, despite having no conscious awareness of seeing them. Usually observed in patients with occipital lobe lesions. Boston Aphasia Classification System A systematic classification of aphasic profiles which can be used to identify aphasia and to predict what profiles of damage a patients might be expected to show when assessing their damage. The Boston Classification System builds on the models of aphasia which were developed by Broca, Wernicke and Lichtheim. Implicit in this approach is the concept that language can be localised in the human brain, and that different profiles of language deficits are related to distinctly different patterns of brain damage. Bottleneck The point in processing where parallel processing becomes serial. Bottom-up (or stimulus-driven) processing Processing which is directed by information contained within the stimulus

Glossary (contrasts with top-down processing). Breakthrough The ability of information to capture conscious awareness despite being unattended. Usually used with respect to the unattended channel in dichotic listening experiments. Broca’s area A region of the brain normally located in the left frontal region, which controls motor speech production. Capture The ability of one source of information to take processing priority from another. For example the sudden onset of novel information within a modality such as an apple falling may interrupt ongoing attentional processing. Cell assembly A group of cells which have become linked to one another to form a single functional network. Proposed by Hebb as a possible biological mechanism underlying the representation and storage of a memory trace. Central executive A hypothetical mechanism which is believed to be in overall control of the working memory. It is assumed to control a variety of tasks, such as decisionmaking, problem-solving and selective attention. Cognitive interview An approach to interviewing eyewitnesses which makes use of the findings of cognitive psychology, such as context reinstatement. Cognitive neuropsychology The study of the brain activities underlying cognitive processes, often by investigating cognitive impairment in brain-damaged patients. Cognitive neuroscience The investigation of human

cognition by relating it to brain structure and function, normally obtained from brain-imaging techniques. Cognitive psychology The study of the way in which the brain processes information. It includes the mental processes involved in perception, learning and memory storage, thinking and language. Comprehension Refers to the outcome of a range of linguistic processes, from acoustic to semantic and syntactic, which contribute to the way that a linguistic message is understood. Computer modelling The simulation of human cognitive processes by computer. Often used as a method of testing the feasibility of an informationprocessing mechanism. Confabulation The reporting of memories which are incorrect and apparently fabricated, but which the patient believes to be true. Congenital prosopagnosia This is thought to be present from birth and is thought to occur without any apparent brain injury. Conjunction A term from feature integration theory of attention that describes a target defined by at least two separable features, such as a red O amongst green O’s and red T’s. Consistent mapping A task in which distractors are never targets and targets are never distracters, so that there is a consistent relationship between the stimuli and the responses to be made to them. Constancy The ability to perceive constant objects in the world despite continual changes in viewing conditions. Constructivist approach Building up our perception

399

of the world from incomplete sensory input. (See also perceptual hypotheses.) Contention scheduler A component of Norman and Shallice’s (1986) model which is responsible for the semi-automatic control of schema activation to ensure that schema run off in an orderly way. Controlled attention Attention processing that is under conscious, intentional control. It requires attentional resources, or capacity, and is subject to interference. Controlled processing Processing that is under conscious control, and which is a relatively slow, voluntary process (contrasts with automatic processing). Covert attentional orienting Orienting attention without making any movement of the eyes. Decision-making This involves making a selection from various options, often in the absence of full information. Declarative memory Memory which can be reported in a deliberate and conscious way (contrasts with procedural memory). Deductive reasoning An approach to reasoning in which conclusions can be judged valid or invalid given that certain statements or premises are assumed to be true. Deductive reasoning task A problem that has a welldefined structure in a system of formal logic where the conclusion is certain. Dementia A persistent impairment in intellectual function due to brain dysfunction, which

400

Glossary

commonly is associated with a progressive loss of function. It is mainly a disease of ageing, being more common in more elderly populations. Dementias can be relatively focal in their effects (e.g. semantic dementia) or more widespread and ‘global’ in their effects (e.g. Alzheimer’s disease). Some dementias primarily affect subcortical regions (e.g. Parkinson’s disease) and other have a more cortical effect (e.g. Pick’s disease). Developmental prosopagnosia This is thought to be a result of early neurological trauma that might be caused by accident or injury Diencephalon A brain structure which includes the thalamus and hypothalamus. Parts of the diencephalon are involved in processing and retrieving memories, and damage to these structures can cause amnesia. Digit span A measure of the largest number of digits which an individual can recall when tested immediately after their presentation. Widely used as a test of the capacity of the phonological component of the working memory. Direct perception Perception without the need for topdown processing. Disinhibition Impaired response inhibition, an inability to suppress previous incorrect responses observed in patients with frontal lobe epilepsy. Dorsal stream A pathway which carries visual information about the spatial location of an object. Double dissociation A method of distinguishing between two functions whereby each

can be separately affected or impaired by some external factor without the other function being affected, thus providing particularly convincing evidence for the independence of the two functions. Dysexecutive syndrome A collection of deficits observed in frontal lobe patients which may include impaired concentration, impaired concept formation, disinhibition, inflexibility, perseveration, impaired cognitive estimation and impaired strategy formation. Dyslexia Developmental difficulties in reading. (See also alexia.) Early selection Selective attention that operates on the physical information available from early perceptual analysis. Easterbrook’s hypothesis The notion that high levels of arousal or anxiety cause a narrowing of attention. Ecological validity The extent to which findings in psychology (especially those obtained in the laboratory) generalise to the real world. Electroconvulsive therapy (ECT) A treatment used to alleviate depression which involves passing an electric current through the front of the patient’s head. Electroencephalography (EEG) Recording the brain’s electrical activity via electrodes placed against the scalp. Can be used to continuously record rhythmic patterns in brain function or particular responses to events (event-related potentials). Encoding The process of transforming a sensory stimulus into a memory trace. Encoding specificity principle (ESP) The theory that

retrieval cues will only be successful in accessing a memory trace if they contain some of the same items of information which were stored with the original trace. Endogenous attention Attention that is controlled by the intention of a participant. Episodic buffer A hypothetical component of working memory which integrates information from different sense modalities, and provides a link with the longterm memory. Episodic memory Memory for specific episodes and events from personal experience, occurring in a particular context of time and place (contrasts with semantic memory). Event-related potentials (ERP) Systematic changes in the brain’s electrical responses linked to the presentation of a stimulus. Typically the stimulus is presented numerous times with the electroencephalographic (EEG) signals time-locked to its occurrence then being averaged to separate the signal from noise. Executive functions Metaabilities necessary for appropriate social functioning and everyday problem-solving, for example the deployment of attention, self-regulation, insight, planning and goal-directed behaviour. Exogenous attention Attention that is drawn automatically to a stimulus without the intention of the participant. Processing by exogenous attention cannot be ignored. Experimental psychology The scientific testing of psychological processes in human and animal subjects.

Glossary Explicit memory Memory which a subject is able to report consciously and deliberately (contrasts with implicit memory). Extended hippocampal complex A system of interconnected structures within the brain, incorporating the hippocampus, anterior thalamus and mammillary bodies, which is involved in the encoding and storage of new memory traces. Familiarity The recognition of an item as one that has been encountered on some previous occasion. Feature detectors Mechanisms in an information-processing device (such as a brain or a computer) which respond to specific features in a pattern of stimulation, such as lines or corners. Feature overlap The extent to which features of the memory trace stored at input match those available in the retrieval cues. According to the encoding specificity principle (ESP), successful retrieval requires extensive feature overlap. Features Elements of a scene that can be extracted and then used to build up a perception of the scene as a whole. (See also geons.) Fixation When the fovea of the eye dwells on a location in visual space, during which time information is collected. Flashbulb memory A subject’s recollection of details of what they were doing at the time of some major news event or dramatic incident. Form agnosia This is now the generally accepted term for patients who are unable to discriminate between objects and are unable to copy line drawings of objects

(this was previously termed apperceptive agnosia). Formants Spectral prominences in spoken language, specific patterns of which are associated with particular speech sounds – thus vowels in English are different in how the formants are spaced across the frequency range. Frontal lobe syndrome The pattern of deficits exhibited by patients with damage to the frontal lobes. These patients are distractible, have difficulty setting, maintaining and changing behavioural goals, and are poor at planning sequences of actions. Functional fixedness The inability to use an object appropriately in a given situation because of prior experience of using the object in a different way. Functional magnetic resonance imaging (fMRI) A medical imaging technology that uses very strong magnetic fields to measure changes in the oxygenation of the blood in the brain and thus map levels of activity in the brain. It produces anatomical images of extremely high resolution. Fusiform face area (FFA) The fusiform area has been shown to be a key structure in face and object processing; numerous studies have shown that the fusiform gyrus contains an area dedicated to face processing – the fusiform face area (FFA). Galvanic skin response A measurable change in the electrical conductivity of the skin when emotionally significant stimuli are presented. Often used to detect the unconscious processing of stimuli. Gaze-mediated orienting An exogenous shift of attention

401

following the direction of gaze of a face presented at fixation. Geons Basically features, but conceived explicitly as being 3-D features. Gestalt psychology An approach to psychology which emphasised the way in which the components of perceptual input became grouped and integrated into patterns and whole figures. Gyrus The surface of the brain is formed by the cerebral cortex, and this has its surface area greatly increased by being thrown into folds. A gyrus is the outer surface of one of these folds, and a sulcus is formed when in the depths of a fold. If the fold in the cortex is very deep it is called a fissure, like the lateral fissure which separates the temporal lobe from the frontal lobe. Haptic perception Tactile (touch) and kinaesthetic (awareness of position and movement of joints and muscles) perception. Herpes simplex encephalitis (HSE) A virus infection of the brain, which in some cases leaves the patient severely amnesic. Heuristics Methods or strategies which often lead to problem solution but are not guaranteed to succeed. Hippocampus A structure lying within the temporal lobes, which is involved in the creation of new memories. Hippocampal lesions usually cause impairment of memory, especially the storage of new memories. Ideomotor compatibility The compatibility between the stimulus and its required response in terms of, usually, spatial relations.

402

Glossary

Illusions Cases in which perception of the world is distorted in some way. Impasse A sort of mental ‘blank’ experienced when trying to solve a problem, which is accompanied by a subjective feeling of not knowing what to do. Implicit memory Memory whose influence can be detected by some indirect test of task performance, but which the subject is unable to report deliberately and consciously (contrasts with explicit memory). Individuation Recognising one specific item from other members of that class of item (e.g. recognising the face of a particular individual). Inductive reasoning task A problem that has a welldefined structure in a system of formal logic where the conclusion is highly probable but not necessarily true. Insight The reorganising or restructuring of the elements of the problem situation in such a way as to provide a solution. Also known as productive thinking. Integrative agnosia This is the generally accepted term for associative agnosia. It refers to patients who can perceive the individual shapes and elements of objects but are unable to integrate these into a representation of the whole object. Interpolation Using computerised image-processing systems to construct images that are intermediate between two other images. Judgement This involves an assessment of the likelihood of an event occurring on the basis of incomplete information; it often forms

the initial process in decisionmaking. Knowledge Information that is not contained within the sensory stimulus. Korsakoff’s syndrome A brain disease which usually results from chronic alcoholism, and which is mainly characterised by a memory impairment. Late selection An account of selective processing where attention operates after all stimuli have been analysed for their semantic properties. Laws of perceptual organisation Principles (such as proximity) by which parts of a visual scene can be resolved into different objects. Lesion Refers to tissue damage – in the brain this can be a result of a stroke, a tumour, an infectious disease, the effects of a toxin, a direct injury or a progressive disease (a dementia). Lexical decision task An experiment in which participants are given a target item (typically written), and asked to decide whether it is a real word or not. Lexical decision tasks are used as the amount of time taken to give a response can indicate how the target item is being processed: this response can be used in combination with other tasks, e.g. priming. Long-term memory Memory held in permanent storage, available for retrieval at some time in the future (contrasts with short-term memory). Long-term potentiation (LTP) A lasting change in synaptic resistance following the application of electrical stimulation to living brain tissue. Possibly one of the biological mechanisms underlying the learning process.

Masking The disruptive effect of an auditory or visual pattern that is presented immediately after an auditory or visual stimulus. This is backward masking, but there are other types of masking. Means–ends analysis A general heuristic where a subproblem is selected that will reduce the difference between the current state and the goal state. Mental model A representation that we construct according to what is described in the premises of a reasoning problem, which will depend on how we interpret these premises. Mental set A term to describe the rote application of one successful method to solve a problem which makes one ‘blind’ to an alternative and possibly much simpler method. Meta-analysis A form of statistical analysis based on combining all the findings in a specific area to obtain an overall picture. Misinformation effect The contamination of eyewitness testimony by information acquired after the witnessed event. Mnemonic A technique or strategy used for improving the memorability of items, for example by adding meaningful associations. Modality The processing system specific to one of the senses, such as vision, hearing or touch. Modular system A system in which different types of processing are carried out by separate and relatively independent sub-systems. Mood-congruent memory The finding that learning and retrieval are better when the

Glossary learner’s (or rememberer’s) mood state is the same as (or congruent with) the affective value of the to-beremembered material. Mood-state-dependent memory The finding that memory performance is better when the individual’s mood state is the same at learning and retrieval than when it differs. Morphemes Units of meaning within words. A word like ‘descendant’ contains a number of morphemes which contribute to its meaning (‘de-’ = from, ‘-scend-’ = climb, ‘-ant’ = person with the property of). Neologisms Non-words which can be used by some neuropsychological patients in place of real words. The patients frequently do not know that they are not using real words. More widely, neologisms are used to refer to new words which are making their way into wider, more commonplace language use. Neurotransmitter A chemical substance which is secreted across the synapse between two neurons, enabling one neuron to stimulate another. Numena The world as it really is. (See also phenomena.) Optimistic bias An individual’s mistaken belief that he/she is more likely than most other people to experience positive events but less likely to experience negative events. Organic amnesia An impairment of memory function caused by physical damage to the brain. Orienting In the spotlight model of visual attention, this is attention to regions of space that does not depend upon eye movements. Orienting task A set of instructions used to influence

the type of cognitive processing employed. Overt attentional orienting Making an eye movement to attend to a location. Pandemonium A fanciful but appealing conceptual model of a feature extraction process. Parallel distributed processing (PDP) approaches Stimuli are represented in the brain, not by single neurons, but by networks of neurons. An approach sometimes used to model cognitive processes. Perception The subjective experience of sensory information after having been subjected to cognitive processing. Perceptual hypotheses An element of the constructivist approach, in which hypotheses as to the nature of a stimulus object are tested against incoming sensory information. Perseveration An inability to shift response strategy characteristic of frontal lobe patients. Phantom word illusion What we hear may be influenced by what we expect to hear. Phenomena Numena as we perceive them. Phenomenological experience Our conscious experience of the world. Phoneme The smallest unit of speech which contributes to its linguistic meaning: changing a phoneme will change the meaning of a word. Phonological loop A hypothetical component of working memory, which is assumed to provide brief storage for verbally presented items. Phonotactics Rules which govern how phonemes can

403

be combined and sequenced in any one language – for example, a syllable can start with ‘dw-’ in English, but a syllable cannot end ‘-dw’. Pop-out An object will pop out from a display if it is detected in parallel and is different from all other items in the display. Positron emission tomography (PET) A method of imaging structure and function in the human brain by directly tracking blood flow using radioactive tracers. PET can be used to form structural images of blood flow in the brain, as the brain is richly supplied with blood. PET can also be used to look at neural activity by tracking local changes in regional cerebral blood flow, which are seen when there is local increased in neural activity. Because the power of PET is limited by the number of scans, and because the number of scans is limited by the amount of radioactivity which can safely be administered, PET is becoming less commonly used for functional imaging studies. Pragmatic reasoning schemata Clusters of rules that are highly generalised and abstracted but defined with respect to different types of relationships and goals. Primal sketch First stage in Marr’s model of vision, which results in computation of edges and other details from retinal images. Problem reduction An approach to problem solving that converts the problem into a number of sub-problems, each of which can be solved separately. Problem space A term introduced by Newell and

404

Glossary

Simon to describe the first stage in problem-solving; represented in the problem space are the initial state, the goal state, the instructions, the constraints on the problem and all relevant information retrieved from long-term memory. Procedural knowledge Unconscious knowledge about how to do something. It includes skills and knowledge that cannot be made explicit but can be demonstrated by performance. Procedural memory Memory which can be demonstrated by performing some skilled procedure such as a motor task, but which the subject is not necessarily able to report consciously (contrasts with declarative memory). Production system A computational model based on numerous IF–THEN condition–action rules. IF the rule is represented in working memory THEN the production stored in longterm memory is applied. Proprioception Knowledge of the position of the body and its parts (arms, fingers, etc.). (See also haptic perception.) Prosopagnosia An inability to recognise faces despite adequate visual acuity. Prototypes Representations of objects in terms of fairly abstract properties. More flexible than templates. Psychogenic amnesia A memory impairment of psychological origin. Psychological refractory period The time delay between the responses to two overlapping signals that reflects the time required for the first response to be organised before the response to the second signal can be organised.

Recency and primacy effects The tendency for participants to show particularly good recall for items presented towards the end (recency) or the start (primacy) of a list. Recollection Remembering a specific event or occasion on which an item was previously encountered. Reconsolidation The finding that the reactivation of a memory makes it temporarily vulnerable to change. Recovered memories Childhood traumatic or threatening memories that are remembered many years after the relevant events or experiences. Re-entrant processing Information flow between brain regions (bidirectional). Regular orthography Refers to a writing system in which there is a direct correspondence between speech sounds and letters. In irregular orthographies, like English, the relationship between speech sounds and letters is more opaque and variable. Rehabilitation Strategies used to help patients to cope with an impairment or disability, enabling them to function as effectively as possible within the limitations created by the impairment. Representativeness heuristic Making judgements on the basis of the extent to which the salient features of an object or person are representative of the features thought to be characteristic of some category. Repression Motivated forgetting of traumatic or other very threatening events (e.g. childhood abuse). Retrieval-induced forgetting (RIF) The phenomenon whereby the successful retrieval of a memory trace

inhibits the retrieval of rival memory traces. Retrograde amnesia (RA) Impaired memory for events which occurred prior to the onset of amnesia (contrasts with anterograde amnesia). Reversible figure A figure in which the object perceived depends on what is designated as ‘figure’ and what is designated as ‘(back)ground’. Saccade The movement of the eyes during which information uptake is suppressed. Between saccades the eye makes fixations during which there is information uptake at the fixated area. Saccadic eye movements Small eye movements which are automatic and involuntary. Schema A mental pattern, usually derived from past experience, which is used to assist with the interpretation of subsequent cognitions, for example by identifying familiar shapes and sounds in a new perceptual input. Scotoma A blind area within the visual field, resulting from damage to the visual system (plural = scotomata). Selection for action The type of attention necessary for planning controlling and executing responses, or actions. Selection for perception The type of attention necessary for encoding and interpreting sensory data. Selective filtering An attentional task that requires selection of one source of information for further processing and report in a difficult task such as dichotic listening or visual search for a conjunction of properties. Selective set An attentional task requiring detection of

Glossary a target from a small set of possibilities. Semantic memory Memory for general knowledge, such as the meanings associated with particular words and shapes, without reference to any specific contextual episode (contrasts with episodic memory). Semantics The meanings of words and the ways that this knowledge is structured and interpreted. Sentences can be ungrammatical but fully semantically comprehensible (e.g. I don’t want you to turn me down! I want you to turn me yes!). Sensation The ‘raw’ sensory input (as compared with perception). Sensory conspicuity The extent to which aspects of a stimulus (such as colour and luminance) influence how easily it can be registered by the senses. (See also attention conspicuity.) Sensory overload A situation in which there is too much incoming sensory information to be adequately processed. Shadowing Used in a dichotic listening task in which participants must repeat aloud the to-be-attended message and ignore the other message. Short-term memory Memory held in conscious awareness, and which is currently receiving attention (contrasts with long-term memory). Sign language A visual language, normally arising in deaf communities, in which the hands are used to express linguistic information. Sign languages are not just sequences of pantomimed gestures, nor are they typically visual forms of existing spoken languages –

for example, British Sign Language has very little in common with spoken British English, having a very different syntax and rules for combining words. In sign language, the face is often used to replace the role of prosody and intonation in spoken language, being used to convey emphasis and emotion. Size constancy The perceived size of objects is adjusted to allow for perceived distance. Slips of action Errors in carrying out sequences of actions, e.g. where a step in the sequence is omitted, or an appropriate action is made, but to the wrong object. Spectral cues Auditory cues to, for example, distance provided by the distortion of the incoming stimulus by (e.g.) the pinnae (ear lobes). Speech Spoken form of a language: a way of conveying linguistic information with the human voice. State–action tree A diagram showing all the possible sequences of actions and intermediate states which can be constructed if the problem is well-defined. Stroke Refers to brain damage which occurs as a result of cardiovascular issues. The brain is an energy intensive organ, using around 20 per cent of the available oxygen circulating in the blood supply. Disruption to blood supply causes brain damage to occur very quickly. The damage can occur due to a blockage in a blood vessel (an ischaemic stroke) or due to a blood vessel rupturing (haemorragic stroke). Strokes are associated with sudden onsets of symptoms of brain damage, and the symptoms

405

can reduce in severity as time passes. Stroop effect The effect of a welllearned response to a stimulus slowing the ability to make the less-well-learned response; for example, naming the ink colour of a colour word. Subliminal Below the threshold for conscious awareness or confident report. Supervisory attentional system A term used by Norman and Shallice to describe a system that can heighten a schema’s level of activation, allowing it to be in a better position to compete with other schemas for dominance and thus increasing its probability of being selected in contention scheduling. Synaesthesia A condition in which individuals presented with sensory input of one modality consistently and automatically experience a sensory event in a different modality (for example seeing colour on hearing musical notes). Synaesthete A person who has the condition synaesthesia. Synapse The gap between the axon of one neuron and the dendrite of another neuron. Syntax Grammatical rules of a language. These rules govern the ways that words can be combined (and declined). Syntax can be independent of meaning: a sentence can be syntactically correct but meaningless (e.g. ‘colourless green dreams sleep furiously’). Templates Stored representations of objects enabling object recognition. Testing effect The finding that actively testing a memory improves its subsequent retrievability.

406

Glossary

Three-dimensional (3-D) sketch Third stage in Marr’s model of vision. This is a viewerindependent representation of the object which has achieved perceptual constancy or classification. Top-down (or schema-driven) processing Processing which makes use of stored knowledge and schemas to interpret an incoming stimulus (contrasts with bottom-up processing). Transcranial magnetic stimulation (TMS) This technique uses an electrical coil placed near the surface of the head to induce a rapid change in the magnetic field, which, in turn, produces a weak electrical current in underlying brain tissue. This can cause depolarisation or hyperpolarisation. The technique can use single bursts or repetitive stimulation. It can be used to support inferences about the role of that brain region in a particular task (e.g. by showing that repetitive stimulation slows responses in task a but not task b, that the region is involved in task a). Two-and-a-half-dimensional (2.5-D) sketch Second stage in Marr’s theory of vision. Aligns details in primal sketch into a viewer-centred representation of the object. Unilateral spatial neglect A difficulty in noticing or

acting on information from one side of space typically caused by a brain lesion to the opposite hemisphere (e.g. right-hemisphere damage producing lack of awareness for information on the left). Also called hemispatial neglect or hemispatial inattention. Urbach–Wiethe disease A disease in which the amygdala and adjacent areas are destroyed; it leads to the impairment of emotional processing and memory for emotional material. Varied mapping The condition in which a stimulus and its response are changed from trial to trial. Ventral stream A pathway in the brain that deals with the visual information for what objects are. Visual masking Experimental procedure of following a briefly presented stimulus by random visual noise or fragments of other stimuli. Interferes with or interrupts visual processing. Visual search Experimental procedure of searching through a field of objects (`distractors’) for a desired object (`target’). Visuo-spatial sketchpad A hypothetical component of working memory, which is assumed to provide brief storage for visually presented items.

Weapon focus The finding that eyewitnesses pay so much attention to some crucial aspect of the situation (e.g. a weapon) that they ignore other details. Wernicke’s area A region of the brain normally located in the left temporal region, which is concerned with the perception and comprehension of speech. Word A word is a lexical unit which can stand alone in terms of its use in a language and its meaning. Words have meanings which map onto things and ideas: words are the level at which languages convey meaning. Word-length effect The finding that word span in immediate recall is greater for short words than for long words. Working memory (WM) A hypothetical short-term memory system which serves as a mental workspace in which a variety of processing operations are carried out on both new input and retrieved memories. Writing A visual system for representing a language. Writing systems can be alphabetic (where one symbol corresponds roughly to one speech sound), syllabic (where one symbol corresponds to one syllable), or ideographic/logographic (where individual symbols correspond to one word).

References Ackerly, S. (1937). Instinctive, emotional and mental changes following prefrontal lobe extirpation. American Journal of Psychiatry, 92, 717–729. Addis, D. R. and Tippett, L. J. (2004). Memory of myself: Autobiographical memory and identity in Alzheimer’s disease. Memory, 12, 56–74. Addis, D. R. and Schacter, D. L. (2012). The hippocampus and imagining the future: Where do we stand? Frontiers in Human Neuroscience, 5(article 173), 1–15. Aggleton, J. P. (2008). Understanding anterograde amnesia: Disconnections and hidden lesions. Quarterly Journal of Experimental Psychology, 61, 1441–1471. Aggleton, J. P. and Saunders, R. C. (1997). Anatomical basis of anterograde amnesia. Memory, 5, 49–71. Aglioti, S., DeSouza, J. F. X. and Goodale, M. A. (1995). Size-contrast illusions deceive the eye but not the hand. Current Biology, 5, 679–685. Albert, M. S., Butters, N. and Levin, J. (1979). Temporal gradients in the retrograde amnesia of patients with alcoholic Korsakoff’s disease. Archives of Neurology, 36, 211–216. Alderman, N., Burgess, P. W., Knight, C. and Henman, C. (2003). Ecological validity of a simplified version of the multiple errands shopping test. Journal of the International Neuropsychological Society, 9, 31–44. Allen, G. A., Mahler, W. A. and Estes, W. K. (1969). Effects of recall tests on long-term retention of paired associates. Journal of Verbal Learning and Verbal Behaviour, 8, 463–470. Altmann, E. M. and Schunn, C. D. (2012). Decay versus interference: A new look at an old interaction. Psychological Science, 23, 1435–1437. Altmann, G. M. T. (1998). Ambiguity in sentence processing. Trends in Cognitive Sciences, 2(4), 146–151. Alzheimer, A. (1907). Uber eine eigenartige Erkranskung der Hirnrinde. Allgemeine Zeitschrift fur Psychiatrie Psychoisch-Gerichliche Medicin, 64, 146–148. Amir, N., Badour, C. L. and Freese, B. (2009). The effect of retrieval on recall of information in

individuals with PTSD. Journal of Anxiety Disorders, 23, 535–540. Amir, N., Leiner, A. S. and Bomyea, J. (2010). Implicit memory and posttraumatic stress symptoms. Cognitive Therapy and Research, 34, 49–58. Amodio, D. M. and Ratner, K. G. (2011). A memory systems model of implicit social cognition. Current Directions in Psychological Science, 20, 143–148. Anderson, B., Mennemeier, M. and Chatterjee, A. (2000). Variability not ability: Another basis for performance decrements in neglect. Neuropsychologia, 38(6), 785–796. Anderson, J. M., Gilmore, R., Roper, S. et al. (1999). Conduction aphasia and the arcuate fasciculus: A reexamination of the Wernicke-Geschwind model. Brain and Language, 70, 1–12. Anderson, J. R. (1980). Cognitive Psychology and Its Implications. San Francisco: W. H. Freeman. Anderson, J. R. (2004). Cognitive Psychology and Its Implications (7th edn). New York: Worth. Anderson, J. R. and Bower, G. H. (1972). Human Associative Memory. Washington, DC: Winston. Anderson, J. R., Fincham, J. M., Qin, Y. and Stocco, A. (2008). A central circuit of the mind. Trends in Cognitive Sciences, 12, 136–143. Anderson, M. C. (2001). Active forgetting: Evidence for functional inhibition as a source of memory failure. Journal of Aggression, Maltreatment, and Trauma, 4, 185–210. Anderson, M. C. (2003). Rethinking interference theory: Executive control and the mechanisms of forgetting. Journal of Memory and Language, 49, 415–445. Anderson, M. C. and Neely, J. H. (1996). Interference and inhibition in memory retrieval. In E. L. Bjork and R. A. Bjork (eds) Memory: Handbook of Perception and Cognition. New York: Academic Press. Anderson, M. C., Bjork, R. A. and Bjork, E. L. (1994). Remembering can cause forgetting: Retrieval dynamics in long-term memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 1063–1087.

408

References

Anderson, M. C., Bjork, R. A. and Bjork, E. L. (2000). Retrieval-induced forgetting: Evidence for a recall-specific mechanism. Journal of Experimental Psychology: Learning, Memory, and Cognition, 7, 522–530. Andrewes, D. (2001). Neuropsychology: From Theory to Practice. Hove: Psychology Press. Andrews, B., Brewin, C. R., Ochera, J., Morton, J., Bekerian, D. A., Davies, G. M. and Mollon, P. (1999). The timing, triggers and qualities of recovered memories in therapy. British Journal of Clinical Psychology, 39, 11–26. Andrews, P. W. and Thomson, J. A. (2009). The bright side of being blue: Depression as an adaptation for analysing complex problems. Psychological Review, 116, 620–654. Andrews, S. (1997). The effects of orthographic similarity on lexical retrieval: Resolving neighborhood conflicts. Psychological Bulletin and Review, 4, 439–461. Anolli, L., Antonietti, A., Crisafulli, L. and Cantoia, M. (2001). Accessing source information in analogical problem solving. The Quarterly Journal of Experimental Psychology, 54A, 237– 261. Asher, J. E., Lamb, J. A., Brocklebank, D., Cazier, J. B. et al. (2009). A whole-genome scan and finemapping linkage study of auditory-visual synesthesia reveals evidence of linkage to chromosomes 2q24, 5q33, 6p12, and 12p12. American Journal of Human Genetics, 84(2), 279–285. Ask, K. and Granhag, P. A. (2007). Hot cognition in investigative judgments: The differential influence of anger and sadness. Law and Human Behavior, 31, 537–551. Aslan, A., Zellner, M. and Bauml, K-H. (2010). Working memory capacity predicts listwise directed forgetting in adults and children. Memory, 18, 442–450. Assal, G., Favre, C. and Anders, J. P. (1984). Nonreconnaissance d’animaux familièrs chez un paysan: Zooagnosie ou prosopagnosia pour les animaux. Revue Neurologique, 140, 580–584. Atkinson, R. C. and Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence and J. T. Spence (eds) The Psychology of Learning and Motivation (Vol. 2). London: Academic Press. Auerbach, S. H., Allard, T., Naeser, M., Alexander, M. P. and Albert, M. L. (1982). Pure word deafness: Analysis of a case with bilateral lesions and a defect at the prephonemic level. Brain, 105, 271–300.

Avidan, G. and Behrmann, M. (2008). Implicit familiarity processing in congenital prosopagnosia. Journal of Neuropsychology, 2(1), 141– 164. doi: 10.1348/174866407X260180. Baddeley, A. D. (1986). Working Memory. Oxford: Oxford University Press. Baddeley, A. D. (1993). Working memory or working attention? In A. Baddeley and L. Weiskrantz (eds) Attention: Selection, Awareness and Control: A Tribute to Donald Broadbent. Oxford: Oxford University Press. Baddeley, A. D. (1995). Memory. In C. C. French and A. M. Colman (eds) Cognitive Psychology. New York: Longman. Baddeley, A. D. (1996). Exploring the central executive. Quarterly Journal of Experimental Psychology, 49A, 5–28. Baddeley, A. D. (1997). Human Memory: Theory and Practice. Hove: Erlbaum. Baddeley, A. D. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences, 4, 417–423. Baddeley, A. D. (2003). Working memory and language: An overview. Journal of Communication Disorders, 36, 189–208. Baddeley, A. D. (2004). The psychology of memory. In A. D. Baddeley, M. D. Kopelman and B. A. Wilson (eds) The Essential Handbook of Memory Disorders for Clinicians. Chichester: Wiley. Baddeley, A. D. (2007). Working Memory, Thought and Action. Oxford: Oxford University Press. Baddeley, A. D. (2009a). Learning. In A. D. Baddeley, M. W. Eysenck and M. C. Anderson (eds) Memory. Hove: Psychology Press. Baddeley, A. D. (2009b). Working memory. In A. D. Baddeley, M. W. Eysenck and M. C. Anderson (eds) Memory. Hove: Psychology Press. Baddeley, A. D. and Warrington, E. K. (1970). Amnesia and the distinction between long- and short-term memory. Journal of Verbal Learning and Verbal Behaviour, 9, 176–189. Baddeley, A. D. and Hitch, G. J. (1974). Working memory. In G. H. Bower (ed.) The Psychology of Learning and Motivation (Vol. 8). London: Academic Press. Baddeley, A. D. and Lewis, V. J. (1981). Inner active processes in reading: The inner voice, the inner ear, and the inner eye. In A. M. Lesgold and C. A. Perfetti (eds) Interactive Processes in Reading. Hillsdale, NJ: Lawrence Erlbaum Associates. Baddeley, A. D. and Wilson, B. (1988). Frontal amnesia and the dysexecutive syndrome. Brain and Cognition, 7, 212–230.

References Baddeley, A. D. and Wilson, B. (1994). When implicit learning fails: Amnesia and the problem of error elimination. Neuropsychologia, 32, 53–68. Baddeley, A. D. and Wilson, B. (2002). Prose recall and amnesia: Implications for the structure of working memory. Neuropsychologia, 40, 1737– 1743. Baddeley, A. D., Thomson, N. and Buchanan, M. (1975). Word length and the structure of shortterm memory. Journal of Verbal Learning and Verbal Behaviour, 14, 575–589. Baddeley, A. D., Lewis, V. J. and Vallar, G. (1984). Exploring the articulatory loop. Quarterly Journal of Experimental Psychology, 36, 233– 252. Baddeley, A. D., Gathercole, S. and Papagno, C. (1998). The phonological loop as a language learning device. Psychological Review, 105, 158–173. Baddeley, A. D., Kopelman, M. D. and Wilson, B. A. (eds) (2004). The Essential Handbook of Memory Disorders for Clinicians. Chichester: Wiley. Baddeley, A. D., Eysenck, M. W. and Anderson, M. C. (2009). Memory. Hove: Psychology Press. Bahrick, H. P., Bahrick, P. O. and Wittlinger, R. P. (1975). Fifty years of memory for names and faces: A cross-sectional approach. Journal of Experimental Psychology: General, 104, 54–75. Bahrick, H. P., Hall, L. K. and Da Costa, L. A. (2008). Fifty years of memory for college grades. Emotion, 8, 13–22. Bailey, C. H. and Kandel, E. R. (2004). The synaptic growth and persistence of long-term memory: A molecular perspective. In M. S. Gazzaniga (ed.) The Cognitive Neurosciences (3rd edn). Cambridge, MA: MIT Press. Bailey, P. J. and Summerfield, Q. (1980). Information in speech: Observations on the perception of [s]stop clusters. Journal of Experimental Psychology: Human Perception and Performance, 6, 536–563. Baizer, J. S., Ungerleider, L. G. and Desimone, R. (1991). Organization of visual inputs to the inferior temporal and posterior parietal cortex in macaques. Journal of Neuroscience, 11(1), 168–190. Balani, A. B., Soto, D. and Humphreys, G. W. (2009). Constraints on task-based control of behaviour following frontal lobe damage: A single-case study. Cognitive Neuropsychology, 26, 635–654. Baldo, J. V., Delis, D. C., Wilkins, D. P. and Shimamura, A. P. (2004). Is it bigger than a

409

breadbox? Performance of patients with prefrontal lesions on a new executive function test. Archives of Clinical Neuropsychology, 19, 407–419. Balota, D. A. and Spieler, D. H. (1998). The utility of item-level analyses in model evaluation: A reply to Seidenberg and Plaut. Psychological Science, 9, 238–240. Balota, D. A., Cortese, H. J. and Pilotti, M. (1999). Item-level analyses of lexical decision performance results from a mega-study. In Abstracts of the 40th Annual Meeting of the Psychonomic Society (p. 44). Los Angeles: Psychonomic Society. Balota, D. A., Cortese, M. J., Sergent-Marshall, S. D., Spieler, D. H. and Yap, M. J. (2004). Visual word recognition of single-syllable words. Journal of Experimental Psychology: General, 133, 283–316. Balota, D. A., Yap, M. J., Cortese, M. J., Hutchison, K. A., Kessler, B., Loftis, B., Neely, J. H., Nelson, D. L., Simpson, G. B. and Treiman, R. (2007). The English Lexicon Project. Behavior Research Methods, 39, 445–459. Bamdad, M. J., Ryan, L. M. and Warden, D. L. (2003). Functional assessment of executive abilities following traumatic brain injury. Brain Injury, 17, 1011–1020. Banich, M. T. (2004). Cognitive Neuroscience and Neuropsychology. Boston, MA: Houghton Mifflin. Banich, M. T. and Compton, R. J. (2010). Cognitive Neuroscience, International Edition (3rd edn). Pacific Grove, CA: Wadsworth. Barceló, F. (1999). Electrophysiological evidence of two different types of error in the Wisconsin card sorting test. Neuroreport, 10, 1299–1303. Barceló, F. and Knight, R. T. (2002). Both random and perseverative errors underlie WCST deficits in prefrontal patients. Neuropsychologia, 40, 349–356. Barceló, F., Sanz, M., Molina, V. and Rubia, F. J. (1997). The Wisconsin Card Sorting Test and the assessment of frontal function: A validation study with event-related potentials. Neuropsychologia, 35, 399–408. Barnett, K. J., Finucane, C., Asher, J. E., Bargary, G., Corvin, A. P., Newell, F. N. and Mitchell, K. J. (2008). Familial patterns and the origins of individual differences in synaesthesia. Cognition, 106(2), 871–893. Barnier, A. J., Conway, M. A., Mayoh, L. and Speyer, J. (2007). Directed forgetting of recently recalled autobiographical memories. Journal

410

References

of Experimental Psychology: General, 136, 301–322. Baron, J. and Strawson, C. (1976). Use of orthographic and word-specific knowledge in reading words aloud. Journal of Experimental Psychology: Human Perception and Performance, 2, 386–393. Baron-Cohen, S. (1992). The theory of mind hypothesis of autism: History and prospects of the idea. The Psychologist, 5, 9–12. Baron-Cohen, S., Wyke, M. A. and Binnie, C. (1987). Hearing words and seeing colours: An experimental investigation of a case of synaesthesia. Perception, 16, 761–767. Baron-Cohen, S., Harrison, J., Goldstein, L. H. and Wyke, M. (1993). Coloured speech perception: Is synaesthesia what happens when modularity breaks down? Perception, 22, 419–426. Baron-Cohen, S., Burt, L., Smith-Laittan, F. and Harrison, J. (1996). Synaesthesia: prevalence and familiarity. Perception, 25, 1073–1080. Bartlett, F. C. (1932). Remembering. Cambridge: Cambridge University Press. Barton, J. J. S. (2008). Structure and function in acquired prosopagnosia: lessons from a series of 10 patients with brain damage. Journal of Neuropsychology, 2(Pt 1), 197–225. Barton, J. J. S., Cherkasova, M. V. and O’Connor, M. (2001). Covert recognition in acquired and developmental prosopagnosia. Neurology, 57, 1161–1168. Barton, J. J. S., Cherkasova, M. V., Press, D. Z., Intriligator, J. M. and O’Connor, M. (2003). Developmental prosopagnosia: A study of three patients. Brain and Cognition, 51, 12–30. Basden, B. H. and Basden, D. R. (1996). Directed forgetting: Further comparisons of the item and list methods. Memory, 4, 633–653. Basso, A., Spinnler, H., Vallar, G. and Zanobio, M. E. (1982). Left hemisphere damage and selective impairment of auditory-verbal short-term memory. Neuropsychologia, 20, 263–274. Bate, S., Haslam, C., Tree, J. J. and Hodgson, T. L. (2008). Evidence of an eye movement-based memory effect in congenital prosopagnosia. Cortex, 44(7), 806–819. Bauer, R. M. (1984). Autonomic recognition of names and faces in prosopagnosia: A neuropsychological application of the Guilty Knowledge Test. Neuropsychologia, 22, 457–469. Bauml, K-H. and Kuhbandner, C. (2007). Remembering can cause forgetting – but not in negative moods. Psychological Science, 18, 111–115.

Bayley, P. J. and Squire, L. R. (2003). The medial temporal lobe and declarative memory. International Congress Series, 1250, 245–259. doi: 10.1016/S0531–5131(03)00192–4. Bearman, C. R., Ball, L. and Ormerod, T. C. (2007). The structure and function of spontaneous analogising in domain-based problem solving. Thinking and Reasoning, 13, 273–294. Bearman, C. R., Ormerod, T. C., Ball, L. and Deptula, D. (2011). Explaining away the negative effects of evaluation on analogical transfer: The perils of premature evaluation. The Quarterly Journal of Experimental Psychology, 64, 942–959. Beck, A. T., Rush, A. J., Shaw, B. F. and Emery, G. (1979). Cognitive Therapy of Depression. New York: Wiley. Beck, D. M., Rees, G., Frith, C. D. and Lavie, N. (2001). Neural correlates of change detection and change blindness. Nature Neuroscience, 4(6), 645–650. Beck, D. M., Muggleton, N., Walsh, V. and Lavie, N. (2005). Right parietal cortex plays a critical role in change blindness. Cerebral Cortex, 15, 1736–1741. Becker, J. T. and Overman, A. A. (2004). The memory deficit in Alzheimer’s disease. In A. D. Baddeley, M. D., Kopelman and B. A. Wilson (eds) The Essential Handbook of Memory Disorders for Clinicians. Chichester: Wiley. Behrmann, M., Avidan, G., Giao, F. and Black, S. (2007). Structural imaging reveals anatomical alterations in inferotemporal cortex in congenital prosopagnosia. Cerebral Cortex, 7(10), 2354–2363. Beilock, S. L., Carr, T. H., MacMahon, C. and Starkes, J. L. (2002). When paying attention becomes unproductive: Impact of divided verus skill-focussed attention in novice and experienced performance in sensorimotor skills. Journal of Experimental Psychology: Applied, 8, 6–16. Bellas, D. N., Novelly, R. A., Eskenazi, B. and Wasserstein, J. (1988). Unilateral displacement in the olfactory sense: A manifestation of the unilateral neglect syndrome. Cortex, 24(2), 267–275. Bellugi, U., Wang, P. P. and Jernigan, T. L. (1994). Williams syndrome: An unusual neuropsychological profile. In S. H. Broman and J. Grafman (eds) Atypical Cognitive Deficits in Developmental Disorders: Implications for Brain Function. Hillsdale, NJ: Laurence Erlbaum. Bench, C. J., Frith, C. D., Grasby, P. M., Friston, K. J., Paulesu, E., Frackowiak, R. S. J. and Dolan,

References R. J. (1993). Investigations of the functional anatomy of attention using the stroop test. Neuropsychologia, 31, 907–922. Bentin, S., DeGutis, J. M., D’Esposito, M. and Robertson, L. C. (2007). Too many trees to see the forest: Performance, event-related potential, and functional magnetic resonance imaging manifestations of integrative congenital prosopagnosia. Journal of Cognitive Neuroscience,19(1), 132–146. Benton, A. L. (1991). The prefrontal region: Its early history. In H. S. Levin, H. M. Eisenberg and A. L. Benton (eds) Frontal Lobe Function and Dysfunction. Oxford: Oxford University Press. Benton, T. R., Ross, D. F., Bradshaw, E., Thomas, W. N. and Bradshaw, G. S. (2006). Eyewitness memory is still not common sense: Comparing jurors, judges and law enforcement to eyewitness experts. Applied Cognitive Psychology, 20, 115–129. Beranek, L. L. (1996). Concert and Opera Halls: How They Sound. Woodbury, NY: Acoustical Society of America. Berntsen, D. and Rubin, D. C. (2004). Cultural life scripts structure recall from autobiographical memory. Memory and Cognition, 32, 427–442. Berti, A. and Rizzolatti, G. (1992). Visual processing without awareness: Evidence from unilateral neglect. Journal of Cognitive Neuroscience, 4, 345–351. Besner, D., Davies, J. and Daniels, S. (1981). Reading for meaning. The effects of concurrent articulation. Quarterly Journal of Experimental Psychology, 33A, 415–437. Bianchi, L. (1922). The Mechanisms of the Brain and the Functions of the Frontal Lobes (translation by J. H. Macdonald). Edinburgh: Livingstone. Biederman, I. (1987). Recognition-by-components: A theory of human image understanding. Psychological Review, 94, 115–147. Bishop, D. V. M. (2006). What causes specific language impairment in children? Current Directions in Psychological Science, 15(5), 217–221. Bisiach, E. and Luzzatti, C. (1978). Unilateral neglect of representational space. Cortex, 14, 129–133. Bjork, R. A. (1972). Theoretical implications of directed forgetting. In A. W. Melton and E. Martin (eds) Coding Processes in Human Memory. Washington, DC: Winston. Bjork, R. A. and Bjork, E. L. (1992). A new theory of disuse and an old theory of stimulus fluctuation.

411

In A. F. Healy, S. M. Kosslyn and R. M. Shiffrin (eds) From Learning Processes to Cognitive Processes: Essays in Honour of William K. Estes (Vol. 2, pp. 35–67). Hillsdale, NJ: Erlbaum. Blackmore, S. (2003). Consciousness: An Introduction. London: Hodder & Stoughton. Blaiss, C. A. and Janak, P. H. (2006). Post-training and post-reactivation administration of amphetamine enhances morphine conditioned place preference. Behavioural Brain Research, 171, 329–337. Blakemore, S. J., Wolpert, D. M. and Frith, C. D. (1998). Central cancellation of self-produced tickle sensation. Nature Neuroscience, 1(7), 635–40. Blanchette, I. and Dunbar, K. (2000). How analogies are generated: The roles of structural and superficial similarity. Memory and Cognition, 28, 108–124. Blanchette, I. and Dunbar, K. (2001). Analogy use in naturalistic settings: The influence of audience, emotion, and goals. Memory and Cognition, 29, 730–735. Blanchette, I. and Richards, A. (2010). The influence of affect on higher level cognition: A review of research on interpretation, judgment, decision making and reasoning. Cognition and Emotion, 24, 561–595. Blanchette, I., Richards, A., Melnyk, L. and Lavda, A. (2007). Reasoning about emotional contents following shocking terrorist attacks: A tale of three cities. Journal of Experimental Psychology: Applied, 13, 47–56. Blank, S. C., Scott, S. K., Murphy, K., Warburton, E. and Wise, R. J. (2002). Speech production: Wernicke, Broca and beyond. Brain, 125, 1829–38. Blesser, B. (1972). Speech perception under conditions of spectral transformation: I. phonetic characteristics. Journal of Speech and Hearing Research, 15, 5–41. Bliss, T. V. P. and Lomo, T. (1973). Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetised rabbit following stimulation of the perforant path. Journal of Physiology, 232, 331–356. Blix, I. and Brennen, T. (2012). Retrieval-induced forgetting after trauma: A study with victims of sexual assault. Cognition and Emotion, 26, 321–331. Bock, J. K. and Levelt, W. J. M. (1994). Language production: Grammatical encoding. In M. A. Gernsbacher (ed.) Handbook of Psycholinguistics. London: Academic Press.

412

References

Bodamer, J. (1947). Die Prosopa-Agnosie. Archiv für Psychiatrie und Nervenkrankheiten, 179, 6–53. Bogen, J. E. and Bogen, G. M. (1976). Wernicke’s region – Where is it? Annals of the New York Academy of Sciences, 280, 834–843. Bornstein, B., Sroka, M. and Munitz, H. (1969). Prosopagnosia with animal face agnosia. Cortex, 5, 164–169. Bottini, G., Karnath, H. O., Vallar, G., Sterzi, R., Frith, C. D., Frackowiak, R. S. J. and Paulesu, E. (2001). Cerebral representations for egocentric space – Functional-anatomical evidence from caloric vestibular stimulation and neck vibration. Brain, 124(6), 1182–1196. Boucher, V. J. (1994). Alphabet-related biases in psycholinguistic enquiries: Considerations for direct theories of speech production and perception. Journal of Phonetics, 22 (1), 1–18. Boutsen, L. and Humphreys, G. W. (2002). Face context interferes with local part processing in a prosopagnosic patient. Neuropsychologia, 40(13), 2305–2313. Bowen, A., McKenna, K. and Tallis, R. C. (1999). Reasons for variability in the reported rate of occurrence of unilateral spatial neglect after stroke. Stroke, 30(6), 1196–1202. Bower, G. H., Monteiro, K. P. and Gilligan, S. G. (1978). Emotional mood as a context for learning and recall. Journal of Verbal Learning and Verbal Behaviour, 17, 573–585. Bowles, D. C., McKone, E., Dawel, A., Duchaine, B., Palermo, R., Schmalzl, L., Rivolta, D. et al. (2009). Diagnosing prosopagnosia: effects of ageing, sex, and participant-stimulus ethnic match on the Cambridge Face Memory Test and Cambridge Face Perception Test. Cognitive Neuropsychology, 26, 423–455. doi:10.1080/ 02643290903343149. Braine, M. D. S. and O’Brien, D. P. (1991). A theory of if: A lexical entry, reasoning program, and pragmatic principles. Psychological Review, 98, 182–203. Braine, M. D. S., Reiser, B. J. and Rumain, B. (1984). Some empirical justification for a theory of natural propositional logic. In G. H. Bower (ed.) The Psychology of Learning and Motivation (Vol. 18, pp. 313–371). New York: Academic Press. Brandt, K. R., Gardiner, J. M., Vargh-Khadem, F., Baddeley, A. D. and Mishkin, M. (2009). Impairment of recollection but not familiarity in a case of developmental amnesia. Neurocase, 15, 60–65. Bransford, J. D. and Johnson, M. K. (1972). Contextual prerequisites for understanding:

Some investigations of comprehension and recall. Journal of Verbal Learning and Verbal Behaviour, 11, 717–726. Brewer, N. and Wells, G. L. (2006). Eyewitness identification. Current Directions in Psychological Science, 20, 24–27. Brewin, C. R. (1998). Intrusive memories, depression, and PTSD. The Psychologist, 11, 281–283. Brickner, R. M. (1936). The Intellectual Functions of the Frontal Lobes. New York: Macmillan. Bridgeman, B. (1992). Conscious vs unconscious processing: The case of vision. Theory and Psychology, 2(1), 73–88. Bridgeman, B., Peery, S. and Anand, S. (1997). Interaction of cognitive and sensorimotor maps of visual space. Perception and Psychophysics, 59(3), 456–469. Bright, D. A. and Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: Anger, blame, and jury decision-making. Law and Human Behavior, 30, 183–202. Broadbent, D. E. (1958). Perception and Communication. Oxford: Pergamon. Broca, P. (1861a). Perte de la parole. Ramollissement chronique et destruction partielle du lobe anterieur gauche du cerveau. Bulletin de la Societe d’Anthropologie (Paris), 2, 235–238. Broca, P. (1861b). Remarques sur le siege de la faculte du language articule, suivies d’ une observation d’ aphemie. Bulletin de la Société d’anthropologie (Paris), 2, 330–357. Brockmole, J. R. and Logie, R. H. (2013). Agerelated change in visual working memory: A study of 55,753 participants aged 8–75. Frontiers of Psychology (29 January). doi: 10.3389.00012. Broeders, R., van den Bos, K., Müller, P. A. and Ham, J. (2011). Should I save or should I not kill? How people solve moral dilemmas depends on which rule is mostaccessible. Journal of Experimental Social Psychology, 47, 923–934. Broman, M. (2001). Spaced retrieval: A behavioural approach to memory improvement in Alzheimer’s and related dementias. NYS Psychologist, 13, 35–40. Brown, A. S. (2002). Consolidation theory and retrograde amnesia in humans. Psychonomic Bulletin and Review, 9, 403–425. Brown, A. S. (2004). The Déjà Vu Experience. Hove: Psychology Press. Brown, A. S. and Murphy, D. R. (1989). Cryptomnesia: Delineating inadvertent plagiarism. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15, 432–442.

References Brown, C., Lloyd-Jones, T. and Robinson, M. (2008). Eliciting person descriptions from eyewitnesses: A survey of police perceptions of eyewitness performance and reported use of interview techniques. European Journal of Cognitive Psychology, 20, 529–560. Brown, J. (1958). Some tests of the decay theory of immediate memory. Quarterly Journal of Experimental Psychology, 10, 12–21. Brown, R. and Kulik, J. (1977). Flashbulb memories. Cognition, 5, 73–99. Bruce, V. and Young, A. (1986). Understanding face recognition. British Journal of Psychology, 77, 305–327. Bruce, V. and Young, A. (2012). Face Perception. Psychology Press: Hove. Bruce, V., Green, P. R. and Georgeson, M. A. (1996). Visual Perception, Physiology, Psychology and Ecology (3rd edn). Hove: Psychology Press. Bruner, J. S., Goodnow, J. J. and Austin, G. A. (1956). A Study of Thinking. New York: Wiley. Bruyer, R. (1991). Covert face recognition in prosopagnosia – A review. Brain and Cognition, 2, 223–335. Bruyer, R., Laterre, C., Seron, X., Feyereisen, P., Strypstein, E., Pierrard, E. and Rectem, D. (1983). A case of prosopagnosia with some preserved covert remembrance of familiar faces. Brain and Cognition, 2, 257–284. Buckner, R. L. (2000). Neuroimaging of memory. In M. S. Gazzaniga (ed.) The New Cognitive Neurosciences (2nd edn). Cambridge, MA: MIT Press. Budson, A. E. and Gold, C. A. (2009). Flashbulb, personal, and event memories in clinical populations. In O. Luminet and A. Curci (eds) Flashbulb Memories: New Issues and Perspectives. Hove: Psychology Press. Bullier, J. and Nowak, L. G. (1995). Parallel versus serial processing: New vistas on the distributed organization of the visual system. Current Opinion in Neurobiology, 5(4), 497–503. Burgess, M. C. R. and Weaver, G. E. (2003). Interest and attention in facial recognition. Perceptual and Motor Skills, 96, 467–480. Burgess, P. W. and Shallice, T. (1994). Fractionation of the frontal-lobe syndrome. Revue de Neuropsychologie, 4, 345–370. Burgess, P. W. and Shallice, T. (1996a). Response suppression, initiation and strategy use following frontal lobe lesions. Neuropsychologia, 34, 263–273. Burgess, P. W. and Shallice, T. (1996b). Bizarre responses, rule detection and frontal lobe lesions. Cortex, 32, 241–259.

413

Burgess, P. W., Alderman, N., Evans, J., Emslie, H. and Wilson, B. A. (1998). The ecological validity of tests of executive function. Journal of the International Neuropsychological Society, 4, 547–558. Burgess, P. W., Alderman, N., Volle, E., Benoit, R. G. and Gilbert, S. J. (2009). Mesulam’s frontal lobe mystery re-examined. Restorative Neurology and Neuroscience, 27, 493–506. Burton, A. M., Young, A. W., Bruce, V., Johnston, R, R. and Ellis, A. W. (1991). Understanding covert recognition. Cognition, 39(2), 129–166. Butterworth, B. (1993). Aphasia and models of language prouction and perception. In Blanken, G., Dittmann, J., Grimm, H., Marshall, J. C., Wallesch, C-W. and de Gruyter, W. (eds) Linguistic Disorders and Pathologies: An International Handbook. Berlin: New York. Byrne, R. M. J. (1989). Suppressing valid inferences with conditionals. Cognition, 31, 61–83. Cahill, L., Babinsky, R., Markowitsch, H. J. and McGaugh, J. L. (1995). The amygdale and emotional memory. Nature, 377, 295–296. Cahir, C. and Thomas, K. (2010). Asymmetric effects of positive and negative affect on decision making. Psychological Reports, 106, 193–204. Camp, G., Pecher, D. and Schmidt, H. G. (2007). No retrieval-induced forgetting using item-specific independent cues: evidence against a general inhibitory account. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 950–958. Campbell, D. (1909). Störungen der Merkfähigkeit und fehlenders Krankheitsgefühl bei einem Fall von Stirnhirntumor. Monatsschrift für Psychiatrie, 26, 33–41. Campbell, R. and Conway, M. A. (1995). Broken Memories. Oxford: Blackwell. Campion, J., Latto, R. and Smith, Y. M. (1983). Is blindsight an effect of scattered light, spared cortex, and near-threshold vision? Behavioural and Brain Sciences, 6, 423–428. Caplan, D., Rochon, E. and Waters, G. S. (1992). Articulatory and phonological determinants of word length effects in span tasks. The Quarterly Journal of Experimental Psychology, 45(2), 177–92. Carpenter, S. (2001). Everyday fantasia: The world of synaesthesia. Monitor on Psychology, 32. Carpenter, S. K. and Pashler, H. (2007). Testing beyond words: Using tests to enhance visuospatial map learning. Psychonomic Bulletin and Review, 14, 474–478. Carpenter, S. K., Pashler, H., Wixted, J. T. and Vul, E. (2008). The effect of tests on learning

414

References

and forgetting. Memory and Cognition, 36, 438–448. Carroll, M., Campbell-Ratcliffe, J., Murnane, H. and Perfect, T. J. (2007). Retrieval-induced forgetting in educational contexts: Monitoring expertise, text integration and text format. European Journal of Cognitive Psychology, 19, 590–606. Cavaco, S., Anderson, S. W., Allen, J. S., CastroCaldas, A. and Damasio, H. (2004). The scope of preserved procedural memory in amnesia. Brain, 127, 1853–1867. Cavenett, T. and Nixon, R. D. V. (2006). The effect of arousal on memory for emotionally-relevant information: A study of skydivers. Behaviour Research and Therapy, 44, 1461–1469. Cermak, L. S. and O’Connor, M. (1983). The anterograde and retrograde retrieval ability of a patient with amnesia due to Encephalitis. Neuropsychologia, 21, 213–234. Chalmers, D. J. (1995). The puzzle of conscious experience. Scientific American, 62–68. Chang, W., Hwang, W. and Ji, Y. G. (2011). Haptic seat interfaces for driver information and warning systems. International Journal of Human– Computer Interaction, 27:12, 1119–1132. Channon, S. and Baker, J. (1994). Reasoning strategies in depression: Effects of depressed mood on a syllogism task. Personality and Individual Differences, 17,707–711. Chase, W. G. and Simon, H. A. (1973a). Perception in chess. Cognitive Psychology, 4, 55–81. Chase, W. G. and Simon, H. A. (1973b). The mind’s eye in chess. In W. G. Chase (ed.) Visual Information Processing. New York: Academic Press. Chen, Z., Mo. L. and Honomichl, R. (2004). Having the memory of an elephant: Long-term retrieval and the use of analogues in problem solving. Journal of Experimental Psychology: General, 133, 415–433. Cheng, P. W. and Holyoak, K. J. (1985). Pragmatic reasoning schemas. Cognitive Psychology, 17, 391–416. Cheng, P. W., Holyoak, K. J., Nisbett, R. E. and Oliver, L. M. (1986). Pragmatic versus syntactic approaches to training deductive reasoning. Cognitive Psychology, 18, 293–328. Cherry, E. C. (1953). Some experiments on the recognition of speech with one and two ears. Journal of the Acoustical Society of America, 25, 975–979. Cherry, K. E., Park, D. C., Frieske, D. A. and Rowley, R. L. (1993). The effect of verbal

Elaborations on memory in young and older adults. Memory and Cognition, 21, 725–738. Chi, M. T. H., Bassok, M., Lewis, M., Reimann, P. and Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13, 145–182. Chi, M. T. H., Feltovich, P. J. and Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152. Chomsky, N. (1957). Syntactic structures. The Hague: Mouton. Chronicle, E. P., MacGregor, J. N. and Ormerod, T. C. (2004). What makes an insight problem? The roles of heuristics, goal conception, and solution recording in knowledge-lean problems. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30, 14–27. Chu, S. and Downes, J. J. (2000). Long live Proust: The odour-cued autobiographical memory bump. Cognition, 75, 41–50. Chun, M. M. and Potter, M. C. (2001). The attentional blink within and across the modalities. In K. Shapiro (ed.) The Limits of Attention: Temporal Constraints in Human Information Processing (pp. 20–30). Oxford: Oxford University Press. Cicerone, K., Lazar, R. and Shapiro, W. (1983). Effects of frontal lobe lesions on hypothesis sampling during concept formation. Neuropsychologia, 21, 513–524. Clancy, S. A. and McNally, R. J. (2005/06). Who needs repression? Normal memory processes can explain “forgetting” of childhood sexual abuse. Scientific Review of Mental Health Practice, 4, 66–73. Claparede, E. (1911). Recognition et moiite. Archives Psychologiques Geneve, 11, 79–90. Clare, L., Wilson, B. A., Breen, E. K. and Hodges, J. R. (1999). Errorless learning of face-name associations in early Alzheimer’s disease. Neurocase, 5, 37–46. Clare, L., Baddeley, A. D., Moniz-Cook, E. and Woods, R. (2003). A quiet revolution. The Psychologist, 16, 250–254. Claret, P. L., Castillob, J. d. D. L. d., Moleónc, J. J. J., Cavanillasc, A. B., Martínc, M. G. and Vargasc, R. G. (2003). Age and sex differences in the risk of causing vehicle collisions in Spain, 1990 to 1999. Accident Analysis and Prevention, 35(2), 261–272. Clark, L. A. and Watson, D. (1991). Tripartite model of anxiety and depression: Psychometric evidence and taxonomic implications. Journal of Abnormal Psychology, 100, 316–336.

References Claxton, G. (1998). Knowing without knowing why. The Psychologist, 11, 217–220. Cleary, A. M., Morris, A. L. and Langley, M. M. (2007). Recognition memory for novel stimuli: The structural regularity hypothesis. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 379–393. Cohen, G. (1983). The Psychology of Cognition (2nd edn). London: Academic Press. Cohen, L., Jobert, A., Le Bihan, D. and Dehaene, S. (2004). Distinct unimodal and multimodal regions for word processing in the left temporal cortex. Neuroimage, 23(4), 1256–1270. Cohen, N. J. and Squire, L. R. (1980). Preserved learning and retention of pattern-analysing skill in amnesia: Dissociation of knowing how and knowing that. Science, 210, 207–210. Cohen, N. J. and Squire, L. R. (1981). Retrograde amnesia and remote memory impairment. Neuropsychologia, 19, 337–356. Cohen, N. J. and Eichenbaum, H. E. (1993). Memory, Amnesia, and the Hippocampal System. Cambridge, MA: MIT Press. Colchester, A., Kingsley, D., Lasserson, D., Kendell, B., Bello, F., Rush, C., Stevens, T., Goodman, G., Heilpern, G., Stanhope, N. and Kopelman, M. D. (2001). Structural MRI volumetric analysis in patients with organic amnesia, 1: Methods and findings, comparative findings across diagnostic groups. Journal of Neurology, Neurosurgery, and Psychiatry, 71, 13–22. Cole, B. L. and Hughes, P. K. (1984). A field trial of attention and search conspicuity. Human Factors, 26(3), 299–313. Coleman, M. D. (2010). Sunk cost, emotion, and commitment to education. Current Psychology, 29, 346–356. Collette, F. and Van der Linden, M. (2002). Brain imaging of the central executive component of working memory. Neuroscience and Biobehavioural Reviews, 26, 105–125. Collette, F., Van der Linden, M., Laureys, S., Delfiore, G., Degueldre, C., Luxen, A. andSalmon, E. (2005). Exploring the unity and diversity of the neural substrates of executive functioning. Human Brain Mapping, 25, 409–423. Coltheart, M. (1980). Deep dyslexia: A righthemisphere hypothesis. In M. Coltheart. K. E. Patterson. and J. C. Marshall (eds) Deep Dyslexia (pp. 326–380). London: Routledge and Kegan Paul. Coltheart, M. T., Davelaar, E., Jonsson, J. and Besner, D. (1977). Access to the internal lexicon.

415

In S. Dornic (ed.) Attention and Performance VI. New York: Academic Press. Coltheart, M., Patterson, K. E. and Marshall, J. C. (1987). Deep dyslexia since 1980. In M. Coltheart, K. E. Patterson and J. C. Marshall (eds) Deep Dyslexia (pp. 407–451). London: Routledge and Kegan Paul. Coltheart, M., Rastle, K., Perry, C., Langdon, R. and Ziegler, J. (2001). DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108(1), 204–256. Conroy, M. A., Hopkins, R. O. and Squire, L. R. (2005). On the contribution of perceptual fluency and priming to recognition memory. Cognitive, Affective, and Behavioural Neuroscience, 5, 14–20. Conway, R. A., Cowan, N. and Bunting, M. F. (2001). The cocktail party revisited: The importance of working memory capacity. Psychonomic Buletin and Review, 8, 331–335. Corbett, F., Jefferies, E., Ehsan, S. and LambonRalph, M. A. (2009). Different impairments of semantic cognition in semantic dementia and semantic aphasia: Evidence from the non-verbal domain. Brain: A Journal of Neurology, 132, 2593–2608. Corbetta, M. and Schulman, G. L. (2002). Control of gaol-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 201–215. Corkin, S. (1968). Acquisition of motor skill after bilateral medial temporal-lobe excision. Neuropsychologia, 6, 255–265. Corkin, S., Amaral, D. G., Gonzalez, R. G., Johnson, K. A. and Hyman, B. T. (1997). H. M.’s medial temporal lobe lesion: Findings from magnetic resonance imaging. Journal of Neuroscience, 17, 3964–3979. Corsi, P. M. (1972). Human memory and the medial temporal region of the brain. Unpublished Thesis, cited in S. Della Sala, C. Gray, A. D. Baddeley, N. Allamano and N. Wilson (1999). Pattern span: A tool for unwelding visuo-spatial memory. Neuropsychologia, 37, 1189–1199. Corteen, R. S. and Wood, B. (1972). Autonomous responses to shock associated words in an unattended channel. Journal of Experimental Psychology, 94, 308–313. Corteen, R. S. and Dunn, D. (1974). Shock associated words in a non-attended message: A test for momentary awareness. Journal of Experimental Psychology, 102, 1143–1144.

416

References

Cosentino, S., Chute, D., Libon, D., Moore, P. and Grossman, M. (2006). How does the brain support script comprehension? A study of executive processes and semantic knowledge in dementia. Neuropsychology, 20, 307–318. Cowan, N. (2005). Working Memory Capacity. New York: Psychology Press. Cowan, N. (2010). The magical mystery four: How is working memory capacity limited, and why? Current Directions in Psychological Science, 19, 51–57. Cowey, A. (2004). The 30th Sir Frederick Bartlett lecture: Fact, artefact, and myth about blindsight. The Quarterly Journal of Experimental Psychology, 57A, 577–609. Cowey, A. and Azzopardi, P. (2001). Is blindsight motion blind? In B. de Gelder, E. de Haan and C. A. Heywood (eds) Out of Mind (pp. 87–103). Oxford: Oxford University Press. Craik, F. I. M. (1970). The fate of items in primary memory. Journal of Verbal Learning and Verbal Behaviour, 9, 143–148. Craik, F. I. M. (1977). Depth of processing in recall and recognition. In S. Dornik (ed.) Attention and Performance (Vol. 6, pp. 679–698). New York: Raven Press. Craik, F. I. M. (2002). Levels of processing: Past, present … and future? Memory, 10, 305–318. Craik, F. I. M. (2007). Encoding: A cognitive perspective. In Roediger, H. L. III, Dudai, Y. and Fitzpatrick, S. M. (eds) Science of Memory: Concepts (pp. 129–135). New York: Oxford University Press. Craik, F. I. M. and Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behaviour, 11, 671–684. Craik, F. I. M. and Tulving, E. (1975). Depth of processing and the retention of words in episodic memory. Journal of Experimental Psychology, General, 104, 268–294. Craik, F. I. M. and McDowd, J. M. (1987). Age differences in recall and recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13, 474–479. Craik, F. I. M. and Bialystock, E. (2006). Planning and task management in older adult cooking breakfast. Memory and Cognition, 34, 1236–1249. Craik, F. I. M., Morris, L. W., Morris, R. G. and Loewen, E. R. (1990). Relations between source amnesia and frontal functioning in older patients. Psychology of Ageing, 5, 148–151. Creem, S. H. and Proffitt, D. R. (1998). Two memories for geographical slant: separation and

interdependence of action and awareness. Psychonomic Bulletin and Review, 5(1), 22–36. Crick, F. (1994). The Astonishing Hypothesis. London: Simon & Schuster. Crick, F. and Koch, C. (1990). Towards a neurobiological theory of consciousness. Seminars in the Neurosciences, 2, 263–275. Crinella, F. M. and Yu, J. (2000). Brain mechanisms and intelligence. Psychometric g and executive function. Intelligence, 27, 299–327. Cutler, A. (1981). Making up materials is a confounded nuisance, or: Will we able to run any psycholinguistic experiments at all in 1990? Cognition, 10, 65–70. Dallenbach, K. M. (1951). A puzzle-picture with a new principle of concealment. American Journal of Psychology, 64, 431–433. Damasio, A. R., Damasio, H. and VanHosen, G. W. (1982). Prosopagnosia: Anatomic basis and behavioural mechanisms. Neurology, 32, 321–341. Dando, C. J., Wilcock, R. and Milne, R. (2009). The cognitive interview: The efficiency of a modified mental reinstatement of context procedure for frontline police investigators. Applied Cognitive Psychology, 23, 138–147. Davidson, P. S. R. and Glisky, E. L. (2002). Is flashbulb memory a special instance of source memory? Evidence from older adults. Memory, 10, 99–111. Davies, S. P. (2000). Move evaluation as a predictor and moderator of success in solutions to wellstructured problems. The Quarterly Journal of Experimental Psychology, 53A, 1186–1201. Davis, D. and Loftus, E. L. (2005). Age and functioning in the legal system: Perception memory and judgement in victims, witnesses and jurors. In I. Noy and W. Karwowski (eds) Handbook of Forensic Human Factors and Ergonomics. London: Taylor & Francis. Davis, D. and Loftus, E. L. (2007). Internal and external sources of misinformation in adult witness memory. In M. P. Toglia, J. D. Read, D. F. Ross and R. C. L. Lindsay (eds) Handbook of Eyewitness Psychology, Vol. 1 (pp. 195–237). Mahwah, NJ: Erlbaum. Davis, M. H., Marslen-Wilson, W. D. and Gaskell, M. G. (2002). Leading up the lexical gardenpath: Segmentation and ambiguity in spoken word recognition. Journal of Experimental Psychology: Human Perception and Performance, 28(1), 218–244. Day, R. H. (1989). Natural and artificial cues, perceptual compromise and the basis of veridical

References and illusory perception. In D. Vickers and P. L. Smith (eds) Human Information Processing: Measures and Mechanisms (pp. 107–109). Amsterdam: Elsevier. De Fockert, J. W., Rees, G., Frith, C. D. and Lavie, N. (2001). The role of working memory in selective attention. Science, 291(5509), 1803–1806. De Graaf, T. A., Hsieh, P-J. and Sack, A. T. (2012). The “correlates” in neural correlates of consciousness. Neuroscience and Biobehavioural Reviews, 36, 191–197. De Groot, A. D. (1965). Thought and Choice in Chess. The Hague: Mouton. De Haan, E. H. F. and Campbell, R. (1991). A fifteen year follow-up of a case of developmental prosopagnosia. Cortex, 27, 489–509. De Haan, E. H. F. and Cowey, A. (2011). On the usefulness of ‘what’ and ‘where’ pathways in vision. Trends in Cognitive Sciences, 15(10), 460–466. De Haan, E. H. F., Young, A. W. and Newcombe, F. (1987). Face recognition without awareness. Cognitive Neuropsychology, 4, 385–415. De Haan, E. H. F., Bauer, R. M. and Greve, K. W. (1992). Behavioural and physiological evidence for covert face recognition in a prosopagnosic patient. Cortex, 28(1), 77–95. De Martino, B., Camerer, C. F. and Adolphs, R. (2010). Amygdala damage eliminates monetary loss aversion. Proceedings of the National Academy of Sciences, 107, 3788–3792. De Monte, V. E., Geffen, G. M. and Kwapil, K. (2005). Test-retest reliability and practice effects of a rapid screen test of mild traumatic brain injury. Journal of Clinical and Experimental Neuropsychology, 27, 624–632. De Neys, W. (2006). Automatic-heuristic and executive-analytic processing during reasoning: Chronometric and dual-task considerations. Quarterly Journal of Experimental Psychology, 59, 1070–1100. De Renzi, E. and di Pellegrino, G. (1998). Prosopagnosia and alexia without object agnosia. Cortex, 34(3), 403–415. De Renzi, E., Gentilini, M. and Barbieri, C. (1989). Auditory neglect. Journal of Neurology, Neurosurgery and Psychiatry, 52, 613–617. De Renzi, E., Faglioni, P., Grossi, D. and Nichelli, P. (1991). Apperceptive and associative forms of prosopagnosia. Cortex, 27, 213–221. De Renzi, E., Perani, D., Carlesimo, G. A., Silveri, M. C. and Fazio, F. (1994). Prosopagnosia can be associated with damage to the right

417

hemisphere – an MRI and PET study and a review of the literature. Neuropsychologia, 32(8), 893–902. De Ruiter, J. P., Mitterer, H. and Enfield, N. J. (2006). Predicting the end of a speaker’s turn; a cognitive cornerstone of conversation. Language, 82(3), 515–535. De Vries, M., Holland, R. W. and Witteman, C. L. M. (2008). Fitting decisions: Mood and intuition vs. deliberative decision strategies. Cognition and Emotion, 22, 931–943. De Zeeuw, C. I. (2007). Plasticity: A pragmatic compromise. In H. L. Roediger III, Y. Dudai and S. M. Fitzpatrick (eds) Science of Memory: Concepts (pp. 83–86). New York: Oxford University Press. Dehane, S. and Naccache, L. (2001). Towards a cognitive neuroscience of consciousness: Basic evidence and a workplace framework. Cognition, 79, 1–37. Delaney, P., Nghiem, K. and Waldum, E. (2009). The selective directed forgetting effect: Can people forget only part of a text? Quarterly Journal of Experimental Psychology, 62, 1542–1550. Delis, D. C., Squire, L. R., Bihrle, A. and Massman, P. (1992). Componential analysis of problem-solving ability: Performance of patients with frontal lobe damage and amnesic patients on a new sorting test. Neuropsychologia, 30, 683–697. Dell, G. S. (1986). A spreading-activation theory of retrieval in sentence production. Psychological Review, 93, 283–321. Dell, G. S. and O’Seaghdha, P. G. (1991). Mediated and convergent lexical priming in language production: A comment on Levelt et al. (1991). Psychological Review, 98, 604–614. Dell, G. S., Schwartz, M. F., Martin, N., Saffran, E. M. and Gagnon, D. A. (1997). Lexical access in aphasic and nonaphasic speakers. Psychological Review, 104(4), 801–838. Della Sala, S., Gray, C., Spinnler and Trivelli, C. (1998). Frontal lobe functioning in man. Archives of Clinical Neuropsychology, 13, 663–682. Deloche, G., Andreewsky, E. and Desi, M. (1982). Surface dyslexia: A case report and some theoretical implications to reading models. Brain and Language, 15(1), 12–31. Derakshan, N. and Eysenck, M. W. (1998). Working-memory capacity in high trait-anxious and repressor groups. Cognition and Emotion, 12, 697–713. Desimone, R. and Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193–222.

418

References

Deutsch, D. (2003). Phantom Worlds and Other Curiosities, Audio CD. Philomel Records. Deutsch, J. A. and Deutsch, D. (1963). Attention, some theoretical considerations. Psychological Review, 70, 80–90. Di Lollo, V., Enns, J. T. and Rensink, R. A. (2000). Competition for consciousness among visual events: The psychophysics of reentrant visual processes. Journal of Experimental Psychology: General, 129(4), 481–507. Dixon, M. J., Smilek, D., Cudahy, C. and Merikle, P. M. (2000). Five plus two equals yellow. Nature, 406, 365–365. Dixon, M. J., Smilek, D. and Merikle, P. M. (2004). Not all synaesthetes are created equal: Projector versus associator synaesthetes. Cognitive, Affective and Behavioral Neuroscience, 4(3), 335–343. Dobler, V. B., Manly, T., Verity, C., Woolrych, J. and Robertson, I. H. (2003). Modulation of spatial attention in a child with developmental unilateral neglect. Developmental Medicine and Child Neurology, 45(4), 282–288. Dobler, V. B., Anker, S., Gilmore, J., Robertson, I. H., Atkinson, J. and Manly, T. (2005). Asymmetric deterioration of spatial awareness with diminishing levels of alertness in normal children and children with ADHD. Journal of Child Psychology and Psychiatry, 46(11), 1230–1248. Dodds, C. M., van Belle, J., Peers, P. V., Duncan, J., Cusack, R. and Manly, T. (2008). Rightward shift in spatial awareness with time-on-task and increased cognitive load. Neuropsychology, 43, 1721–1728. Dodson, C. S. and Krueger, L. E. (2006). I misremember it well: Why older adults are unreliable witnesses. Psychonomic Bulletin and Revue, 13, 770–775. Drace, S., Desrichard, O., Shepperd, J. A. and Hoorens, V. (2009). Does mood really influence comparative optimism? Tracing an elusive effect. British Journal of Social Psychology, 48, 579–599. Driver, J. (2001). A selective review of selective attention from the past century. British Journal of Psychology, 92, 53–78. Driver, J. and Halligan, P. W. (1991). Can visual neglect operate in object-centred co-ordinates? An affirmative single-case study. Cognitive Neuropsychology, 8, 475–496. Driver, J. and Spence, C. J. (1994). Spatial synergies between auditory and visual attention. In C. Umilta and M. Moscovitch (eds) Attention and Performance XV, Conscious and Nonconscious

Information Processing. Cambridge, MA: MIT Press. Driver, J. and Spence, C. J. (1998). Cross-modal links in spatial attention. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 353(1373), 1319– 1331. Driver, J. and Spence, C. J. (1999). Cross-modal links in spatial attention. In G. W. Humphreys, J. Duncan and A. Treisman (eds) Attention, Space and Action. Oxford: Oxford University Press. Driver, J., Davis, G., Ricciardelli, P., Kidd, P., Maxwell, E. and Baron-Cohen, S. (1999). Gaze perception triggers visuo-spatial orienting. Visual Cognition, 6(5), 509–540. Dronkers, N. F. (1996). A new brain region for coordinating speech articulation. Nature, 14, 384(6605), 159–61. Drosopoulos, S., Wagner, U. and Born, J. (2005). Sleep enhances explicit recollection in recognition memory. Learning and Memory, 12, 44–51. Duchaine, B. (2000). Developmental prosopagnosia with normal configural processing. Neuroreport, 11, 79–83. Duchaine, B. and Garrido, L. (2008). We’re getting warmer – characterizing the mechanisms of face recognition with acquired prosopagnosia: A comment on Riddoch et al. (2008). Cognitive Neuropsychology, 25(5), 765–8. doi:10.1080/ 02643290802092102. Duchaine, B., Yovel, G., Butterworth, E. J. and Nakayama, K. (2006). Prosopagnosia as an impairment to face-specific mechanisms: Elimination of the alternative hypotheses in a developmental case. Cognitive Neuropsychology, 23(5), 714–47. doi:10.1080/02643290500441296. Duffy, P. L. (2002). Blue Cats and Chartreuse Kittens: How Synesthetes Color Their Worlds. New York: Henry Holt. Dumay, N., Frauenfelder, U. H. and Content, A. (2002). The role of the syllable in lexical segmentation in French: Word-spotting data. Brain and Language, 81, 144–161. Dunbar, R. I. M., Duncan, N. and Nettle, D. (1995). Size and structure of freely forming conversational groups. Human Nature, 6(1), 67–78. Dunbar, R. I. M., Duncan, N. D. C. and Marriott, A. (1997). Human conversational behaviour. Human Nature, 8, 231–246. Duncan, J. (2006). EPS mid-career award (2004). Brain mechanisms of attention. Quarterly Journal of Experimental Psychology, 59, 2–27.

References Duncan, J. and Humphreys, G. W. (1989). Visual search and visual similarity. Psychological Review, 96, 433–458. Duncan, J. and Humphreys, G. W. (1992). Beyond the search surface: Visual search and attentional engagement. Journal of Experimental Psychology: Human Perception and Performance, 18, 578–588. Duncan, J., Emslie, H. and Williams, P. (1996). Intelligence and the frontal lobe: The organization of goal-directed behavior. Cognitive Psychology, 30, 257–303. Duncker, K. (1945). On problem solving. Psychological Monographs, 58 (Whole No. 270). Dupoux, E., Kakehi, K., Hirose, Y., Pallier, C. and Mehler, J. (1999). Epenthetic vowels in Japanese: A perceptual illusion? Journal of Experimental Psychology – Human Perception and Performance, 25(6), 1568–1578. Durie, B. (2005). Doors of perception. New Scientist, 185(2484), 34–36. Easterbrook, J. A. (1959). The effect of emotion on cue utilisation and the organisation of behaviour. Psychological Review, 66, 183–201. Ebbinghaus, H. (1885). Uber das Gedachtnis: Untersuchugen zur Experimentellen Psychologie. Leipzig: Dunker and Humbolt. Edgar, G. K., Edgar, H. E. and Curry, M. B. (2003). Using Signal Detection Theory to Measure Situation Awareness in Command and Control. Paper presented at the Human Factors and Ergonomics Society 47th Annual Meeting, Denver, Colorado. Edquist, J., Rich, A. N., Brinkman, C. and Mattingley, J. B. (2006). Do synaesthetic colours act as unique features in visual search? Cortex, 42(2), 222–231. Edworthy, J., Hellier, E. J., Walters, K., CliftMatthews, W. and Crowther, M. (2003). Acoustic, semantic and phonetic influences in spoken warning signal words. Applied Cognitive Psychology, 17, 915–933. Egeth, H. E. and Yantis, S. (1997). Visual attention: control, representation, and time course. Annual Review of Psychology, 48, 269–297. Eich, E. (1995). Searching for mood-dependent memory. Psychological Science, 6, 67–75. Eichenbaum, H. (2004). Hippocampus: Cognitive processes and neural representations that underlie declarative memory. Neuron, 44, 109–120. Eichenbaum, H., Yonelinas, A. P. and Ranganath, C. (2007). The medial temporal lobe and recognition memory. Annual Review of Neuroscience, 30, 123–152.

419

Eisner, F. and McQueen, J. M. (2005). The specificity of perceptual learning in speech processing. Perception and Psychophysics, 67(2), 224–238. Eisner, F. and McQueen, J. M. (2006). Perceptual learning in speech: Stability over time (L). Journal of the Acoustical Society of America, 119(4), 1950–1953. Ellis, A. W. and Young, A. W. (1996). Human Cognitive Neuropsychology: A Textbook With Readings. Psychology Press. Endler, J. A., Endler, L. C. and Doerr, N. R. (2010). Great bowerbirds create theaters with forced perspective when seen by their audience. Current Biology, 20(18), 1679–1684. Enns, J. T. and Di_Lollo, V. (2000). What’s new in visual masking? Trends in Cognitive Sciences, 4(9), 345–352. Eriksen, B. A. and Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target in a non-search task. Perception and Psychophysics, 16, 143–149. Eriksen, C. W. and St. James, J. D. (1986). Visual attention within and around the field of focal attention: A zoom lens model. Perception and Psychophysics, 40, 225–240. Esgate, A. and Groome, D. H. (2005). An Introduction to Applied Cognitive Psychology. Hove: Psychology Press. Eskes, G. A., Szostak, C. and Stuss, D. T. (2003). Role of the frontal lobes in implicit and explicit retrieval tasks. Cortex, 39, 847–869. Eslinger, P. J. and Damasio, A. R. (1985). Severe disturbance of higher cognition after bilateral frontal lobe ablation: Patient E. V. R. Neurology, Cleveland, 35, 1731–1741. Evans, J. St. B. T. (1989). Bias in Human Reasoning: Causes and Consequences. Hove: Erlbaum. Evans, J. St. B. T. (2003). In two minds: dual process accounts of reasoning. Trends in Cognitive Sciences, 7, 454–459. Evans, J. St. B. T. (2009). How many dual-process theories do we need: One, two or many? In J. St. B. T. and K. Frankish (eds) In Two Minds: Dual Processes and Beyond (pp. 31–54). Oxford: Oxford University Press. Evans, J. St. B. T. (2011). Dual-process theories of reasoning: Contemporary issues and developmental applications. Developmental Review, 31, 86–102. Evans, J. St. B. T. and Lynch, J. S. (1973). Matching bias in the selection task. British Journal of Psychology, 64, 391–397. Evans, J. St. B. T. and Over, D. E. (1996). Rationality and Reasoning. Hove: Psychology Press.

420

References

Evans, J. St. B. T. and Over, D. E. (2004). If. Oxford: Oxford University Press. Evans, J. St. B. T. and Ball, L. J. (2010). Do people reason on the Wason selection task? A new look at the data of Ball et al. (2003). The Quarterly Journal of Experimental Psychology, 63, 434–441. Evans, J. St. B. T., Barston, J. L. and Pollard, P. (1983). On the conflict between logic and belief in syllogistic reasoning. Memory and Cognition, 11, 295–306. Evans, J. St. B. T., Handley, S. J. and Over, D. E. (2003). Conditionals and conditional probability. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 321–335. Evans, S., Kyong, J. S., Rosen, S., Golestani, N., Warren, J. E., McGettigan, C., MourãoMiranda, J., Wise, R. J. and Scott, S. K. (2013). The Pathways for Intelligible Speech: Multivariate and Univariate Perspectives. Cerebral Cortex (12 April). Eysenck, M. W. (1979). Depth, elaboration, and distinctiveness. In L. S. Cermak and F. I. M. Craik (eds) Levels of Processing in Human Memory. Hillsdale, NJ: Lawrence Erlbaum Associates. Eysenck, M. W. (1992). Anxiety: The Cognitive Perspective. Hove: Psychology Press. Eysenck, M. W. (1997). Anxiety and Cognition: A Unified Theory. Hove: Psychology Press. Eysenck, M. W. (2012). Fundamentals of Cognition (2nd edn). Hove: Psychology Press. Eysenck, M. W. and Calvo, M. G. (1992). Anxiety and performance: The processing efficiency theory. Cognition and Emotion, 6, 409–434. Eysenck, M. W. and Keane, M. T. (2005). Cognitive Psychology: A Student’s Handbook. Hove: Psychology Press. Eysenck, M. W. and Keane, M. T. (2010). Cognitive Psychology: A Student’s Handbook (6th edn). Hove: Psychology Press. Eysenck, M. W., Payne, S. and Santos, R. (2006). Anxiety and depression: Past, present, and future events. Cognition and Emotion, 20, 274–294. Eysenck, M. W., Derakshan, N., Santos, R. and Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7, 336–353. Farah, M. J. (2004). Visual Agnosia (2nd edn). Cambridge, MA: MIT Press. Farah, M. J. and McClelland, J. L. (1991). A computational model of semantic memory impairment: Modality-specificity and emergent

category-specificity. Journal of Experimental Psychology: General, 120, 339–357. Farah, M. J., Hammond, K. M., Levind, D. N. and Calvanio, R. (1988). Visual and spatial mental imagery: Dissociable systems of representation. Cognitive Psychology, 20, 439–462. Farah, M. J., Hammond, K. M., Mehta, Z. and Ratcliff, G. (1989). Category-specificity and modality-specificity in semantic memory. Neuropsychologia, 27, 193–200. Farah, M. J., McMullen, P. A. and Meyer, M. M. (1991). Can recognition of living things be selectively impaired? Neuropsychologia, 29, 185–193. Farah, M. J., Levinson, K. L. and Klein, K. L. (1995). Face perception and within-category discrimination in prosopagnosia. Neuropsychologia, 33, 661–674. Feinberg, T., Gonzalez-Rothi, L. J. and Heilman, K. M. (1986). Multimodal agnosia from a unilateral left hemisphere lesion. Neurology, 36, 864–867. Felleman, D. J. and Van Essen, D. C. (1991). Distributed hierarchical processing in primate visual cortex. Cerebral Cortex, 1, 1–47. Ferrier, D. (1876). The Functions of the Brain. London: Smith, Elder. Fiedler, K., Nickel, S., Muehifriedel, T. and Unkelbach, C. (2001). Is mood congruity an effect of genuine memory or response bias? Journal of Experimental Social Psychology, 37, 201–214. Fillmore, C. J. (1968). The case for case. In E. Bach and R. T. Harms (eds) Universals in Linguistic Theory (pp. 1–88). New York: Holt, Rinehart, and Winston. Fimm, B., Willmes, K. and Spijkers, W. (2006). The effect of low arousal on visuo-spatial attention. Neuropsychologia, 44(8), 1261–1268. Finn, B. and Roediger, H. L. III. (2011). Enhancing retention through reconsolidation: Negative emotional arousal flowing retrieval enhances later recall. Psychological Science, 22, 781–786. Fisher, R. P. and Craik, F. I. M. (1977). Interaction between encoding and retrieval operations in cued recall. Journal of Experimental Psychology: Human Learning and Memory, 3, 701–711. Fisher, R. P., Geiselman, R. E. and Amador, M. (1990). A field test of the cognitive interview: Enhancing the recollections of actual victims and witnesses of crime. Journal of Applied Psychology, 74, 722–727. Fisher, R. P., Milne, R. and Bull, R. (2011). Interviewing cooperative witnesses. Current Directions in Psychological Science, 2016–19.

References Fitch, G. M., Hankey, J. M., Kleiner, B. M. and Dingus, T. A. (2011). Driver comprehension of multiple haptic seat alerts intended for use in an integrated collision avoidance system. Transportation Research Part F, 14, 278–290. Fitts, P. M. and Posner, M. I. (1973). Human Performance. Basic Concepts in Psychology series. London: Prentice Hall. Fleischman, D. A., Wilson, R. S., Gabrieli, J. D. E., Bienias, J. L. and Bennett, D. A. (2004). A longitudinal study of implicit and explicit memory loss in old persons. Psychology and Ageing, 19, 617–625. Flin, R., Boon, J., Knox, A. and Bull, R. (1992). The effect of a five-month delay on children’s and adult’s eyewitness memory. British Journal of Psychology, 83, 323–336. Fodor, J. A. (1983). Modularity of Mind. Cambridge, MA: MIT Press. Fornazzari, L., Fischer, C. E., Ringer, L. and Schweizer, T. A. (2011). ‘Blue is music to my ears’: Multimodal synesthesias after a thalamic stroke. Neurocase, 18(4), 318–322. Forster, S. and Lavie, N. (2007). High perceptual load makes everybody equal: Eliminating individual differences in distractibility with load. Journal of Experimental Psychology: Applied, 14, 73–83. Franz, V. H., Gegenfurtner, K. R., Bülthoff, H. H. and Fahle, M. (2000). Grasping visual illusions: No evidence for a dissociation between perception and action. Psychological Science, 11, 20–25. Frassinetti, F., Angeli, V., Meneghello, F., Avanzi, S. and Ladavas, E. (2002). Long-lasting amelioration of visuospatial neglect by prism adaptation. Brain, 125, 608–623. Frazier, L. (1979). On Comprehending Sentences: Syntactic Parsing Strategies. Bloomington: Indiana University Linguistics Club. Freund, C. S. (1889). Uber optische Aophasie und Seelenblindheit. Archiv für Psychiatrie und Nervenkrankheiten, 20, 276–297. Frijda, N. (1986). The Emotions. Cambridge: Cambridge University Press. Friederici, A. D., Rüschemeyer, S. A., Hahne, A. and Fiebach, C. J. (2003). The role of left inferior frontal and superior temporal cortex in sentence comprehension: Localizing syntactic and semantic processes. Cerebral Cortex, 13(2), 170–177. Friedman, N. P., Miyake, A., Corley, R. P., Young, S. E., DeFries, J. C. and Hewitt, J. K. (2006). Not all executive functions are related to intelligence. Psychological Science, 17, 172–179.

421

Friedman, N. P., Miyake, A., Young, S. E., DeFries, J. C., Corley, R. P. and Hewitt, J. K. (2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology: General, 137, 201–225. Friesen, C. K. and Kingstone, A. (1998). The eyes have it! Reflexive orienting is triggered by nonpredictive gaze. Psychonomic Bulletin and Review, 5, 331–342. Fromkin, V. (1971). The non-anomalous nature of anomalous utterances. Language, 47(1), 27–52. Fromkin, V. (1973). Speech Errors as Linguistic Evidence. The Hague: Mouton. Fukuda, K., Vogel, E., Mayr, U. and Awh, E. (2010). Quantity, not quality: The relationship between fluid intelligence and working memory capacity. Psychonomic Bulletin and Review, 17, 673– 679. Funnell, E. and Sheridan, J. (1992). Categories of knowledge? Unfamiliar aspects of living and nonliving things. Cognitive Neuropsychology, 9, 135–153. Gabbert, F., Hope, L. and Fisher, R. P. (2009). Protecting eyewitness evidence: Examining the efficacy of a self-administered interview tool. Law and Human Behaviour, 33, 298–307. Gable, P. and Harmon-Jones, E. (2010). The blues broaden but the nasty narrows: Attentional consequences of negative affects low and high in motivational intensity. Psychological Science, 21, 211–215. Gabrieli, J. D. E., Cohen, N. J. and Corkin, S. (1988). The acquisition of lexical and semantic knowledge in amnesia. Society for Neuroscience Abstracts, 9, 328. Gaffan, D., Parker, E. and Easton, A. (2001). Dense amnesia in the monkey after transaction of the fornix, amygdala and anterior stem. Neuropsychologia, 39, 51–70. Gainotti, G., Barbier, A. and Marra, C. (2003). Slowly progressive defect in recognition of familiar people in a patient with right anterior temporal atrophy. Brain, 126, 792–803. Gaissert, N. and Wallraven, C. (2012). Categorizing natural objects: A comparison of the visual and the haptic modalities. Experimental Brain Research, 216, 123–134. Gale, M. and Ball, L. J. (2009). Exploring the determinants of dual goal facilitation in a rule discovery task. Thinking and Reasoning, 15, 294–315. Galetta, K. M., Barrett, J., Allen, M. et al. (2011). The King-Devick test as a determinant of head

422

References

trauma and concussion in boxers and MMA fighters. Neurology, 76, 1456–1462. Galfano, G., Dalmaso, M., Marzoli, D., Pavan, G., Coricelli, C. and Castelli, L. (2012). Eye gaze cannot be ignored (but neither can arrows). The Quarterly Journal of Experimental Psychology, 65 (10), 1895–1910. Gallace, A. and Spence, C. (2005). Examining the crossmodal consequences of viewing the MullerLyer illusion. Experimental Brain Research, 162, 4, 490–496. Galton, F. (1883). Inquiries Into Human Faculty and Its Development. London: Macmillan. Gardiner, J. M. (2002). Episodic memory and autonoetic consciousness: A first person approach. In A. Baddeley, M. Conway and J. Aggleton (eds) Episodic Memory: New Directions in Research. Oxford: Oxford University Press. Gardiner, J. M. and Parkin, A. J. (1990). Attention and recollective experience in recognition. Memory and Cognition, 18, 579–583. Gardiner, J. M. and Java, R. I. (1993). Recognising and remembering. In R. F. Collins, S. E. Gathercole, M. A. Conway and P. E. Morris (eds) Theories of Memory. Hove: Lawrence Erlbaum Associates. Gardiner, J. M., Brandt, K. R., Baddeley, A. D. VarghaKhadem, F. and Mishkin, M. (2008). Charting the acquisition of semantic knowledge in a case of developmental amnesia. Neuropsychologia, 46, 2865–2868. Gardner, M. B. and Gardner, R. S. (1973). Problem of localization in the median plane: Effect of pinnae cavity. Journal of the Acoustical Society of America, 53, 400–408. Garrett, M. (1975). The analysis of sentence production. In G. H. Bower (ed.) The Psychology of Learning and Motivation (Vol. 9, pp. 133–177). New York: Academic Press. Garrett, M. (1988). Processes in language production. In F. Newmeyer (ed.) Linguistics: The Cambridge Survey III. Language: Psychological and Biological Aspects. Cambridge: Cambridge University Press. Garrido, L., Eisner, F., McGettigan, C., Stewart, L., Sauter, S., Hanley, J. R., Schweinberger, S. R., Warren, J. D. and Duchaine, B. C. (2009). Developmental phonagnosia: A selective deficit of vocal identity recognition. Neuropsychologia, 47(1), 123–131. Garrod, S. and Pickering, M. J. (2004). Why is conversation so easy? Trends in Cognitive Sciences, 8, 8–11. Gathercole, S. E. and Baddeley, A. D. (1989). Development of vocabulary in children and

short-term phonological memory. Journal of Memory and Language, 28, 200–213. Gathercole, S. E. and Baddeley, A. D. (1990). Phonological memory deficits in language disordered children: Is there a causal connection? Journal of Memory and Language, 29, 336–360. Gathercole, S. E., Service, E., Hitch, G., Adams, A. M. and Martin, A. J. (1999). Phonological short-term memory and vocabulary development: Further evidence on the nature of the relationship. Applied Cognitive Psychology, 13, 65–77. Gazzaniga, M. S., Ivry, R. B. and Mangun, G. R. (2009). Cognitive Neuroscience: The Biology of the Mind (2nd edn). New York: W. W. Norton. Geiselman, R. E. (1999). Commentary on recent research with the cognitive interview. Psychology, Crime, and Law, 5, 197–202. Geiselman, R. E. and Fisher, R. P. (1997). Ten years of cognitive interviewing. In D. G. Payne and F. G. Conrad (eds) Intersections in Basic Memory Research. Mahwah, NJ: Erlbaum. Geiselman, R. E., Bjork, R. A. and Fishman, D. L. (1983). Disrupted retrieval in directed forgetting: A link with posthypnotic amnesia. Journal of Experimental Psychology: General, 112, 58–72. Geiselman, R. E., Fisher, R. P., MacKinnon, D. P. and Holland, H. L. (1985). Eyewitness memory enhancement in police interview: Cognitive retrieval mnemonics versus hypnosis. Journal of Applied Psychology, 70, 401–412. Gentner, D. and Gentner, D. R. (1983). Flowing waters and teeming crowds: Mental models of electricity. In D. Genter and A. L. Stevens (eds) Mental Models. Hillsdale, NJ: Lawrence Erlbaum Associates. Gentner, D., Loewenstein, J. and Thompson, L. (2003). Learning and transfer: A general role for analogical encoding. Journal of Educational Psychology, 95, 393–408. George, M., Dobler, V., Nicholls, E. and Manly, T. (2005). Spatial awareness, alertness, and ADHD: the re-emergence of unilateral neglect with time-on-task. Brain and Cognition, 57(3), 264–275. George, M. S., Mercer, J. S., Walker, R. and Manly, T. (2008). A demonstration of endogenous modulation of unilateral spatial neglect: The impact of apparent time-pressure on spatial bias. Journal of the International Neuropsychological Society, 14(1), 33–41. Geraerts, E. (2012). Cognitive underpinnings of recovered memories of childhood abuse. Nebraska Symposium on Motivation, 58, 175–191.

References Geraerts, E., Schooler, J. W., Merckelbach, H., Jelicic, M., Hauer, B. J. and Ambadar, Z. (2007). The reality of recovered memories: Corroborating continuous and discontinuous memories of childhood sexual abuse. Psychological Science, 18, 564–568. Gernsbacher, M. A. (1984). Resolving 20 years of inconsistent interactions between lexical familiarity and orthography, concreteness and polysemy. Journal of Experimental Psychology: General, 113, 256–281. Geschwind, N., Quadfasel, F. A. and Segarra, J. M. (1968). Isolation of the speech area. Neuropsychologia, 6, 327–340. Gibson, J. J. (1950). The Perception of the Visual World. Boston, MA: Houghton Mifflin. Gibson, J. J. (1966). The Senses Considered as Perceptual Systems. Boston, MA: Houghton Mifflin. Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Hillsdale, NJ: Lawrence Erlbaum Associates. Gick, M. L. and Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology, 12, 306–355. Gick, M. L. and Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15, 1–38. Gilhooly, K. J. (1996). Thinking: Directed, Undirected and Creative (3rd edn). London: Academic Press. Gilhooly, K. J., Phillips, L. H., Wynn, V., Logie, R. H. and Della Sala, S. (1999). Planning processes and age in the 5 disk Tower of London task. Thinking and Reasoning, 5, 339–361. Glanzer, M. and Cunitz, A. R. (1966). Two storage mechanisms in free recall. Journal of Verbal Learning and Verbal Behaviour, 5, 351–360. Glenberg, A. M., Smith, S. M. and Green, C. (1977). Type 1 rehearsal: Maintenance and more. Journal of Verbal Learning and Verbal Behaviour, 16, 339–352. Glisky, E. L., Schacter, D. L. and Tulving, E. (1986). Computer learning by memory-impaired patients: Acquisition and retention of complex knowledge. Neuropsychologia, 24, 313–328. Gloning, I., Gloning, K., Hoff, H. (1963). Aphasia: A clinical syndrome. In L. Halpern (ed.) Problems of Dynamic Neurology (pp. 63–70). Jerusalem: Hebrew University. Gluck, J. and Bluck, S. (2007). Looking back over the life span: A life story account of the reminiscence bump. Memory and Cognition, 35, 1928–1939.

423

Godden, D. R. and Baddeley, A. D. (1975). Contextdependent memory in two natural environments: On land and under water. British Journal of Psychology, 66, 325–331. Godden, D. R. and Baddeley, A. D. (1980). When does context influence recognition memory? British Journal of Psychology, 71, 99–104. Goel, V. and Grafman, J. (1995). Are the frontal lobes implicated in “planning” functions? Interpreting data from the Tower of Hanoi. Neuropsychologia, 33, 623–642. Gold, J. M., Hahn, B., Zhang, W. W., Robinson, B. M., Kappenman, E. S., Beck, V. M. and Luck, S. J. (2010). Reduced capacity but spared precision and maintenance of working memory representations in schizophrenia. Archives of General Psychiatry, 67, 570–577. Goldman-Rakic, P. S. (1987). Circuitry of primate prefrontal cortex and regulation of behavior by representational knowledge. In F. Plum and V. Mountcastle (eds) Handbook of Physiology (Vol. 5, pp. 373–417). Bethesda, MD: American Physiological Society. Goldstein, E. B. (2002). Sensation and Perception. Pacific Grove, CA: Wadsworth. Goldstein, E. B. (2009). Sensation and Perception, International Edition (8th edn). Pacific Grove, CA: Wadsworth. Goltz, F. (1892). Der Hund ohne Grosshirn: Siebente Abteilung über die Verrichtungen des Grosshirns. Pfuger‘s Archiv für die Gesamte Physiologie, 51, 570–614. Gonnerman, L. M., Seidenberg, M. S. and Andersen, E. S. (2007). Graded semantic and phonological similarity effects in priming: Evidence for a distributed connectionist approach to morphology. Journal of Experimental Psychology: General, 136, 323–345. Goodale, M. A. (2008). Action without perception in human vision. Cognitive Neuropsychology, 25(7– 8), 891–919. doi:10.1080/02643290801961984. Goodale, M. A. and Milner, A. D. (1992). Separate visual pathways for perception and action. Trends in Neurosciences, 15(1), 20–25. Goodale, M. A. and Milner, A. D. (2004). Sight Unseen: An Exploration of Conscious and Unconscious Vision. Oxford: Oxford University Press. Goodglass, H. and Kaplan, E. (1972). The Assessment of Aphasia and Related Disorders. Philadelphia: Lea and Febiger. Goodwin, D. W., Powell, B., Bremer, D., Hoine, H. and Stern, J. (1969). Alcohol and recall: State dependent effects in man. Science, 163, 1358.

424

References

Gopie, N., Craik, F. I. M. and Hasher, L. (2011). A double dissociation of implicit and explicit memory in younger and older adults. Psychological Science, 22, 634–640. Gorelick, E. D. and Ross, E. D. (1987). The aprosodias: Further functional-anatomic evidence for the organization of affective language in the right hemisphere. Journal of Neurology, Neurosurgery and Psychiatry, 50, 553–560. Gorman, Michael E. and Gorman, Margaret E. (1984). A comparison of disconfirmation, confirmation and control strategy on Wason’s 2–4–6 task. Quarterly Journal of Experimental Psychology, 36A, 629–648. Goswami, U. (2010). A temporal sampling framework for developmental dyslexia. Trends in Cognitive Sciences, 15, 3–10. Goswami, U., Thomson, J., Richardson, U., Stainthorp, R., Hughes, D., Rosen, S. and Scott, S. K. (2002). Amplitude envelope onsets and developmental dyslexia: A new hypothesis. Proceedings of the National Academy of Sciences of the USA, 99(16), 10911–10916. Gotlib, I. H. and Joormann, J. (2010). Cognition and depression: Current status and future directions. Annual Review of Clinical Psychology, 6, 285–312. Gough, P. and Cosky, M. (1977). One second of reading again. In N. Castellan, D. Pisoni and G. Potts (eds) Cognitive Theory (Vol. 2). Hillsdale, NJ.: Erlbaum. Graf, P. and Schacter, D. L. (1985). Implicit and explicit memory for novel associations in normal and amnesic subjects. Journal of Experimental Psychology: Learning, Memory, and Cognition, 11, 501–518. Graf, P., Squire, L. R. and Mandler, G. (1984). The information that amnesic patients do not forget. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 164–178. Graham, K. S., Kropelnicki, A., Goldman, W. P. and Hodges, J. R. (2003). Two further investigations of autobiographical memory in semantic dementia. Cortex, 39, 729–750. Graham, K. S., Lee, A. C. H. and Barense, M. D. (2008). Impairments in visual discrimination in amnesia: Implications for theories of the role of medial temporal lobe regions in human memory. European Journal of Cognitive Psychology, 20, 655–696. Greene, J. D. (2007). Why are VMPFC patients more utilitarian? A dual-process theory of moral judgment explains. Trends in Cognitive Sciences, 11, 322–323.

Greene, J. D., Nystrom, L. E., Engell, A. D., Darley, J. M. and Cohen, J. D. (2004). The neural bases of cognitive conflict and control in moral judgment. Neuron, 44, 389–400. Greenough, W. T. (1987). Experience effects on the developing and the mature brain: Dendritic branching and synaptogenesis. In N. A. Krasnegor, E. Blass, M. Hofer and W. P. Smotherman (eds) Perinatal Development: A Psychobiological Perspective. New York: Academic Press. Greenspoon, J. and Ranyard, R. (1957). Stimulus conditions and retroactive inhibition. Journal of Experimental Psychology, 53, 55–59. Greenwald, A. G. and Shulman, H. G. (1973). On doing two things at once: II. Elimination of the psychological refractory period. Journal of Experimental Psychology, 101, 70–76. Greenwald, A. G. and Banaji, M. R. (1995). Implicit social cognition: Attitudes, self-esteem, and stereotypes. Psychological Review, 102, 4–27. Gregory, R. (1966). Eye and Brain. London: Weidenfield & Nicolson. Gregory, R. L. (1980). Perceptions as hypotheses. Philosophical Transactions of the Royal Society of London, B290, 181–197. Gregory, R. L. (1997). Knowledge in perception and illusion. Philosophical Transactions of the Royal Society London B, 352, 1121–1128. Grice, H. P. (1975). Logic and conversation. In P. Cole and J. Morgan (eds) Syntax and Semantics (Vol. 3, pp. 41–58). New York: Academic Press. Griffin, Z. M. and Crew, C. M. (2012). Research in language production. In M. J. Spivey, K. McRae and M. Joanisse (eds) Cambridge Handbook of Psycholinguistics. Cambridge University Press. Griffiths, T. D., Rees, A. and Green, G. G. R. (1999). Disorders of human complex sound processing. Neurocase, 5(5), 365–378. Griggs, R. A. and Cox, J. R. (1982). The elusive thematic materials effect in the Wason selection task. British Journal of Psychology, 73, 407– 420. Griggs, R. A. and Cox, J. R. (1983). The effects of problem content and negation on Wason’s selection task. Quarterly Journal of Experimental Psychology, 35A, 519–533. Grimm, J. L. C. and Grimm, W. C. (1909). Grimm’s Fairy Tales (trans. E. Lucas). London: Constable and Co. Ltd. Griskevicius, V., Shiota, M. N. and Neufeld, S. L. (2010). Influence of different positive emotions on persuasive processing: A functional evolutionary approach. Emotion, 10, 190–206.

References Groome, D. and Grant, N. (2005). Retrievalinduced forgetting is inversely related to everyday cognitive failures. British Journal of Psychology, 96, 313–319. Groome, D. and Sterkaj, F. (2010). Retrievalinduced forgetting and clinical depression. Cognition and Emotion, 24, 63–70. Grossenbacher, P. G. and Lovelace, C. T. (2001). Mechanisms of synaesthesia: Cognitive and physiological constraints. Trends in Cognitive Sciences, 5, 36–41. Habib, R., McIntosh, A. R., Wheeler, M. A. and Tulving, E. (2003). Memory encoding and hippocampally-based novelty/familiaritydiscrimination networks. Neuropsychologia, 41, 271–279. Hall, D. A., Johnsrude, I. S., Haggard, M. P., Palmer, A. R., Akeroyd, M. A. and Summerfield, A. Q. (2002). Spectral and temporal processing in human auditory cortex. Cerebral Cortex, 12 (2), 140–149. Halstead, W. C. (1940). Preliminary analysis of grouping behaviour in patients with cerebral injury by the method of equivalent and nonequivalent stimuli. American Journal of Psychiatry, 96, 1263–1294. Handy, T. C., Grafton, S. T., Shroff, N. M., Ketay, S. and Gazzaniga, M. S. (2003). Graspable objects grab attention when the potential for action is recognized. Nature Neuroscience, 6, 421–427. Happé, F. (1999). Autism: Cognitive deficit or cognitive style? Trends in Cognitive Sciences, 3, 216–222. Harding, A., Halliday, G., Caine, D. and Kril, J. (2000). Degeneration of anterior thalamic nuclei differentiates alcoholics with amnesia. Brain, 123, 141–154. Hareli, S. and Weiner, B. (2002). Dislike and envy as antecedents of pleasure at another’s misfortune. Motivation and Emotion, 26, 257–277. Harenski, C. L., Keith, A., Shane, M. S. and Kiehl, K. A. (2010). Aberrant neural processing of moral violations in criminal psychopaths. Journal of Abnormal Psychology, 119, 863–874. Harley, T. (2001). The Psychology of Language. Sussex: Psychology Press. Harlow, J. M. (1848). Passage of an iron bar through the head. Boston Medican and Surgical Journal, 39, 389–393. Harlow, J. M. (1868). Recovery from the passage of an iron bar through the head. Publications of the Massachusetts Medical Society, 2, 327–347. Hart, J. and Kraut, M. A. (2007). Neural Basis of Semantic Memory. Cambridge: Cambridge University Press.

425

Hartley, T., Bird, C. M., Chan, D., Cipolotti, L., Husain, M., Vargha-Khadem, F. et al. (2007). The hippocampus is required for shortterm topographical memory in humans. Hippocampus, 17, 34–48. Hastorf, A. H. and Cantril, H. (1954). They saw a game: A case study. Journal of Abnormal and Social Psychology, 49, 129–134. Hauser, M. (2006). Moral Minds: How Nature Designed Our Universal Sense of Right and Wrong. New York: Ecco. Hawkins, S. (2003). Roles and representations of systematic fine phonetic detail in speech understanding. Journal of Phonetics, 31, 373–405. Haxby, J. V., Horwitz, B., Ungerleider, L. G., Maisog, J. M., Pietrini, P. and Grady, C. L. (1994). The functional organization of human extrastriate cortex: a PET-rCBF study of selective attention to faces and locations. Journal of Neuroscience, 14, 6336–6353. Haxby, J., Hoffman, E. and Gobbini, M. (2000). The distributed human neural system for face perception. Trends in Cognitive Sciences, 4(6), 223–233. Retrieved from http://www.ncbi.nlm. nih.gov/pubmed/10827445. Hayashi, T., Umeda, C. and Cook, N. D. (2007). An fMRI study of the reverse perspective illusion. Brain Research, 1163, 72–78. Hayes, J. R. and Simon, H. A. (1974). Understanding written problem instructions. In L. W. Gregg (ed.) Knowledge and Cognition. Hillsdale, NJ: Lawrence Erlbaum Associates. Hayman, C. A. G. and Tulving, E. (1989). Is priming in fragment completion based on a “traceless” memory system? Journal of Experimental Psychology: Learning, Memory, and Cognition, 15, 941–956. Haynes, J. D. and Rees, G. (2005). Predicting the orientation of invisible stimuli from activity in human primary visual cortex. Nature Neuroscience, 8, 686–691. Head, H. (1926). Aphasia and Kindred Disorders of Speech (Vol. 1, pp. 54–60). Cambridge: Cambridge University Press. Heathcote, D. (2005). Working memory and performance limitations. In A. Esgate and D. H. Groome (eds) An Introduction to Applied Cognitive Psychology. Hove: Psychology Press. Hebb, D. O. (1949). The Organisation of Behaviour. New York: Wiley. Heilman, K. M. (2006). Aphasia and the diagram makers revisited: An update of information processing models. Journal of Clinical Neurology, 2(3), 149–162.

426

References

Heilman, K. M., Tucker, D. M. and Valenstein, E. A. (1976). A case of mixed transcortical aphasia with intact naming. Brain, 99, 415–525. Heilman, K. M., Gonzalez-Rothi, L. J., McFarling, D. and Rottman, A. (1981). Transcortical sensory aphasia with relatively spared spontaneous speech in naming. Archives of Neurology, 38, 236–239. Heller, M. A. Brackett, D. D. Wilson, K. Yoneyama, K. and Boyer, A. (2002). The haptic Muller-Lyer illusion in sighted and blind people. Perception, 31, 1263–1274. Helmstaedter, C., Kemper, B. and Elger, C. E. (1996). Neuropsychological aspects of frontal lobe epilepsy. Neuropsychologia, 34, 399–406. Henriques, D. Y. and Soechting, J. F. (2003). Bias and sensitivity in the haptic perception of geometry. Experimental Brain Research, 150, 95–108. Henson, R. N. A., Burgess, N. and Frith, C. D. (2000). Recoding, storage, rehearsal, and grouping in verbal short-term memory: An fMRI study. Neuropsychologia, 38, 426–440. Herrmann, D., Raybeck, D. and Gruneberg, M. (2002). Improving Memory and Study Skills: Advances in Theory and Practice. Ashland OH: Hogrefe and Huber. Hersh, N. and Treadgold, L. (1994). Neuropage: The rehabilitation of memory dysfunction by prosthetic memory and cueing. NeuroRehabilitaion, 4, 187–197. Hickok, G. and Poeppel, D. (2004). Dorsal and ventral streams: A framework for understanding aspects of the functional anatomy of language. Cognition, 92, 67–99. Hickok, G. and Poeppel, D. (2007). The cortical organization of speech processing. Nature Reviews Neuroscience, 8(5), 393–402. Hickok, G., Erhard, P., Kassubek, J., Helms-Tillery, A. K., Naeve-Velguth, S., Strupp, J. P. et al. (2000). A functional magnetic resonance imaging study of the role of left posterior superior temporal gyrus in speech production: Implications for the explanation of conduction aphasia. Neuroscience Letters, 287, 156–60. Hill, C., Memon, A. and McGeorge, P. (2008). The role of confirmation bias in suspect interviews: A systematic evaluation. Legal and Criminological Psychology, 13, 357–371. Hill, E. (2004). Executive dysfunction in autism. Trends in Cognitive Sciences, 8, 26–32. Hills, B. L. (1980). Vision, visibility and perception in driving. Perception, 9, 183–216. Hinton, G. E. and Shallice, T. (1991). Lesioning an attractor network: Investigations of acquired dyslexia. Psychological Review, 98(1), 74–95.

Hiraoka, K., Suzuki, K., Hirayama, K. and Mori, E. (2009). Visual agnosia for line drawings and silhouettes without apparent impairment of real-object recognition: A case report. Behavioural Neurology, 21(3), 187–92. doi:10.3233/BEN-2009–0244. Ho, C. E. (1998). Letter recognition reveals pathways of second-order and third-order motion. Proceedings of the National Academy of Sciences of the United States of America, 95(1), 400–404. Ho, C. and Spence, C. (2005). Assessing the effectiveness of various auditory cues in capturing a driver’s visual attention. Journal of Experimental Psychology Applied, 11, 3, 157–174. Hodges, J. R., Patterson, K. and Tyler, L. K. (1994). Loss of semantic memory: Implications for the modularity of mind. Cognitive Neuropsychology, 11, 505–542. Hofman, P. A. M. Verhay, F. R. J. Wilmink, J. T. Rozandaal, N. and Jolles, J. (2002). Brainlesions in patients visiting a memory clinic with postconcussional sequelae after mild to moderate brain injury. Journal of Neuropsychiatry and Clinical Neurosciences, 14, 176–184. Holland, A. C. and Kensinger, E. A. (2010). Emotion and autobiographical memory. Physics of Life Reviews, 7, 88–131. Horowitz, M. J. (1976). Stress Response Syndromes. New York: Aronson. Howell, P. (2011). Listen to the lessons of The King’s Speech. Nature, 470, 7. Hubbard, E. M. and Ramachandran, V. S. (2005). Neurocognitive mechanisms of synesthesia. Neuron, 48(3), 509–520. Hubel, D. H. and Wiesel, T. N. (1959). Receptive fields of single neurons in the cat’s striate cortex. Journal of Physiology, 148, 574–591. Hulme, C., Maughan, S. and Brown, G. D. A. (1991). Memory for familiar and unfamiliar words: Evidence for a long-term memory contribution to short-term memory span. Journal of Memory and Language, 30, 685–701. Hulme, C., Suprenant, A. M., Bireta, T. J., Stuart, G. and Neath, I. (2004). Abolishing the wordlength effect. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30, 98–106. Humphreys, G. W. and Riddoch, M. J. (1987). To See or Not to See: A Case Study of Visual Agnosia. London: Lawrence Earlbaum Associates. Humphreys, G. W. and Riddoch, M. J. (2006). Features, objects, action: The cognitive neuropsychology of visual object processing, 1984–2004.

References Cognitive Neuropsychology, 23(1), 156–83. doi:10.1080/02643290542000030. Hunt, R. R. (2013). Precision memory through distinctive processing. Current Directions in Psychological Science, 22, 10–15. Hunt, R. R. and McDaniel, M. A. (1993). The enigma of organisation and distinctiveness. Journal of Memory and Language, 32, 421– 445. Hupbach, A., Gomez, R., Hardt, O. and Nadel, L. (2007). Reconsolidation of episodic memories: A subtle reminder triggers integration of new information. Learning and Memory, 14, 47–53. Hupe, J. M., James, A. C., Payne, B. R., Lomber, S. G., Girard, P. and Bullier, J. (1998). Cortical feedback improves discrimination between figure and ground by V1, V2 and V3 neurons. Nature, 394, 784–787. Hupe, J. M., Bordier, C. and Dojat, M. (2012). The neural bases of grapheme-color synesthesia are not localized in real color-sensitive areas. Cerebral Cortex, 22(7), 1622–1633. Huppert, F. A. and Piercy, M. (1976). Recognition memory in amnesic patients: Effect of temporal context and familiarity of material. Cortex, 4, 3–20. Huppert, F. A. and Piercy, M. (1978). The role of trace strength in recency and frequency judgements by amnesic and control subjects. Quarterly Journal of Experimental Psychology, 30, 346–354. Husserl, E. (1931). Ideas: General Introduction to Pure Phenomenology (Vol. 1). New York: Macmillan. Hyde, T. S. and Jenkins, J. J. (1973). Recall for words as a function of semantic, graphic, and syntactic orienting tasks. Journal of Verbal Learning and Verbal Behaviour, 12, 471–480. Hyden, H. (1967). Biochemical and molecular aspects of learning and memory. Proceedings of the American Philosophical Society, 111, 347–351. Jacobsen, C. F., Wolfe, J. B. and Jackson, T. A. (1935). An experimental analysis of the functions of the frontal association areas in primates. Journal of Nervous and Mental Disease, 82, 1–14. Jacoby, L. L. and Dallas, M. (1981). On the relationship between autobiographical memory and perceptual learning. Journal of Experimental Psychology: General, 3, 3006–3040. Jacquemot, C. and Scott, S. K. (2006). What is the relationship between phonological short-term memory and speech processing? Trends in Cognitive Sciences, 10(11), 480–486. Jacquemot, C., Pallier, C., Lebihan, D., Dehaene, S. and Dupoux, E. (2003). Phonological grammar

427

shapes the auditory cortex: A functional Magnetic Resonance Imaging study. Journal of Neuroscience, 23(29), 9541–9546. James, W. (1890). Principles of Psychology. New York: Holt. Jansma, J. M., Ramsey, N. F., Slagter, H. A. and Kahn, R. S. (2001). Fuctional anatomical correlates of controlled and automatic processing. Journal of Cognitive Neuroscience, 13, 730–743. Janssen, S. M. J., Rubin, D. L. and Conway, M. A. (2012). The reminiscence bump in the temporal distribution of the best football players of all time: Pele, Cruijff or Maradonna? Quarterly Journal of Experimental Psychology, 65, 165–178. Janssen, W. and Nilsson, L. (1993). Behavioral effects of driver support. In A. M. Parkes and S. Franzen (eds) Driving Future Vehicles (pp. 147– 155). London: Taylor & Francis. Jared, D., McRae, K. and Seidenberg, M. S. (1990). The basis of consistency effects in word naming. Journal of Memory and Language, 29, 687–715. Jastrowitz, M. (1888). Beiträge zur Localisation im Grosshirn und über deren praktische Verwerthung. Deutsche Medizinische Wochenschrift, 14, 81–83, 108–112, 125–128, 151–153, 172–175, 188–192, 209–211. Jerabek, I. and Standing, L. (1992). Imagined test situations produce contextual memory enhancement. Perceptual and Motor Skills, 75, 400. Jewanski, J., Day, S. A. and Ward, J. (2009). A colorful albino: The first documented case of synaesthesia, by Georg Tobias Ludwig Sachs in 1812. Journal of the History of the Neurosciences, 18(3), 293–303. Joanisse, M. F. and Seidenberg, M. S. (1999). Impairments in verb morphology following brain injury: A connectionist model. Proceedings of the National Academy of Sciences of the USA, 96, 7592–7597. Johnson, A., Johnson, O. and Baksh, M. (1986). The colours of emotions in Machiguenga. American Anthropologist, 88, 674–681. Johnson, J. A. and Zartorre, R. J. (2006). Neural substrates for dividing and focussing attention between simultaneous auditory and visual events. Neuroimage, 31, 27–64. Johnson-Laird, P. N. (1983). Mental Models. Cambridge, MA: Harvard University Press. Johnson-Laird, P. N. and Wason, P. C. (1970). Insight into a logical relation. Quarterly Journal of Experimental Psychology, 22, 49–61. Johnson-Laird, P. N., Legrenzi, P. and Legrenzi, M. S. (1972). Reasoning and a sense of reality. British Journal of Psychology, 63, 395–400.

428

References

Johnson-Laird, P. N., Byrne, R. M. J. and Schaeken, W. (1992). Propositional reasoning by model. Psychological Review, 99, 418–439. Johnson-Laird, P. N., Mancini, F. and Gangemi, A. (2006). A hyper-emotion theory of psychological illnesses. Psychological Review, 113, 822–841. Johnstone, E. C., Deakin, J. F. W., Lawler, P., Frith, C. D., Stevens, M., McPherson, K. et al. (1980). The Northwick Park ECT trial. The Lancet, 1317–1320. Johnstone, L. (2003). A shocking treatment? The Psychologist, 16, 236–239. Joseph, R. (1999). Frontal lobe psychopathology: Mania, depression, confabulation, catatonia, perseveration, obsessive compulsions, and schizophrenia. Psychiatry – Interpersonal and Biological Processes, 62(2), 138–172. Juhasz, B. J. (2005). Age-of-acquisition effects in word and picture identification. Psychological Bulletin, 131(5), 684–712. Jung, R. E. and Haier, R. J. (2007). The parietofrontal integration theory (P-FIT) of intelligence: Converging neuroimaging evidence. Behavioural and Brain Sciences, 30, 135–154. Kaas, J. H. and Hackett, T. A. (1999). “What” and “where” processing in auditory cortex. Nature Neuroscience, 2(12), 1045–1047. Kahneman, D. (1973). Attention and Effort. Englewood Cliffs, NJ: Prentice Hall. Kahneman, D. and Treisman, A. M. (1984). Changing views of attention and automaticity. In R. Parsuraman and D. R. Davies (eds) Varieties of Attention. Orlando, FL. Academic Press. Kahneman, D. and Frederick, S. (2002). Representativeness revisited: Attribute substitution in intuitive judgement. In T. Gilovich, D. Griffin and D. Kahneman (eds) Heuristics and Biases: The Psychology of Intuitive Judgment (pp. 49–81). Cambridge: Cambridge University Press. Kane, M. J. and Engle, R. W. (2002). The role of prefrontal cortex in working memory capacity, executive attention, and general fluid intelligence: An individual differences perspective. Psychonomic Bulletin and Review, 9, 637–671. Kanwisher, N., McDermott, J. and Chun, M. M. (1997). The fusiform face area: A module in human extrastriate cortex specialized for face perception. The Journal of Neuroscience, 17(11), 4302–4311. Retrieved from http:// www.ncbi.nlm.nih.gov/pubmed/9151747. Kapur, N., Ellison, D. Smith, M. McLellan, D. L. and Burrows, E. H. (1992). Focal retrograde amnesia following bilateral temporal lobe pathology. Brain, 115, 73–85.

Kapur, N., Thompson, C., Cook, P., Lang, D. and Brice, J. (1996). Anterograde but not retrograde memory loss following combined mammilary body and medial thalamic lesions. Neuropsychologia, 34, 2–8. Kapur, N., Glisky, E. L. and Wilson, B. A. (2004). External memory aids and computers in memory rehabilitation. In A. D. Baddeley, M. D. Kopelman and B. A. Wilson (eds) The Essential Handbook of Memory Disorders for Clinicians. Chichester: Wiley. Karat, J. (1982). A model of problem-solving with incomplete constraint knowledge. Cognitive Psychology, 14, 538–559. Karnath, H. O. (1997). Spatial orientation and the representation of space with parietal lobe lesions. [Comparative Study]. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 352(1360), 1411–1419. Karnath, H. O., Christ, K. and Hartje, W. (1993). Decrease of contralateral neglect by neck muscle vibration and spatial orientation of trunk midline. Brain, 116, 383–396. Katz, R. B. and Goodglass, H. (1990). Deep dysphasia: Analysis of a rare form of repetition disorder. Brain and Language, 39, 153–185. Keane, M. T. G. (1987). On retrieving analogues when solving problems. Quarterly Journal of Experimental Psychology, 39A, 29–41. Keane, M. T. G. (1990). Incremental analogizing: theory and model. In K. J. Gilhooly, M. T. G. Keane, R. H. Logie and G. Erdos (eds) Lines of Thinking: Reflections on the Psychology of Thought, Vol. 1: Representation, Reasoning, Analogy and Decision Making. Chichester: John Wiley. Kelley, L. A. and Endler, J. A. (2012). Illusions create mating success in great bowerbirds. Science, doi: 10.1126/science.12124. Kelly, J. and Local, J. L. (1986). Long-domain resonance patterns in English. In Proceedings International Conference on Speech Input/ Output (pp. 304–308). London: IEE. Kenealy, P. M. (1997). Mood-state-dependent retrieval: The effects of induced mood on memory reconsidered. Quarterly Journal of Experimental Psychology, 50A, 290–317. Kensinger, E. A., Addis, D. R. and Atapattu, R. K. (2011). Amygdala activity at encoding corresponds with memory vividness and with memory for select episodic details. Neuropsychologia, 49, 663–673. Keren, G. and Schul, Y. (2009). Two is not always better than one: A critical evaluation of two-system

References theories. Perspectives on Psychological Science, 4, 533–550. Kertesz, A., Sheppard, A., MacKenzie, R. (1982). Localization in transcortical sensory aphasia. Archives of Neurology, 39(8), 475–478. Kihlstrom, J. F. and Schacter, D. L. (2000). Functional amnesia. In F. Boller and J. Grafman (eds) Handbook of Neuropsychology (Vol. 2, pp. 409–427). Amsterdam: Elsevier. Kimball, J. (1973). Seven principles of surface structure parsing in natural language. Cognition, 2, 15–47. Kimberg, D. Y. and Farah, M. J. (1993). A unified accound of cognitive impairments following frontal lobe damage: The role of working memory in complex, organized behavior. Journal of Experimental Psychology: General, 122, 411–428. King, J. A., Trinkler, I., Hartley, T., Vargha-Khadem, F. and Burgess, N. (2004). The hippocampal role in spatial memory and the familiarity-recollection distinction: A case study. Neuropsychology, 18, 405–417. King, N. S. and Kirwilliam, S. (2011). Permanent post-concussion symptoms after mild head injury. Brain Injury, 25, 462–470. Kinsbourne, M. (1977). Hemi-neglect and hemisphere rivalry. In E. A. Weinstein and R. P. Friedland (eds) Advances in Neurology (Vol. 18, pp. 41–49). New York: Raven. Kintsch, W. (1968). Recognition and free recall in organised lists. Journal of Experimental Psychology, 78, 481–487. Kirdendall, D. T. and Garrett, W. E. (2001). Heading in soccer: Integral skill or grounds for cognitive dysfunction? Journal of Athletic Training, 36, 328–333. Klatzky, R. L. Lederman, S. J. and Metzger, V. (1987). Identifying objects by touch: An “expert” system. Perception and Psychophysics, 37, 299–302. Klauer, K. C. and Zhao, Z. (2004). Double dissociations in visual and spatial short-term memory. Journal of Experimental Psychology: General, 133, 355–381. Klein, D. E. and Murphy, G. L. (2001). The representation of polysemous words. Journal of Memory and Language, 45, 259–282. Knoblich, G., Ohlsson, S., Haider, H. and Rhenius, D. (1999). Constraint relaxation and chunk decomposition in insight problem solving. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25, 1534–1556. Knoblich, G., Ohlsson, S. and Raney, G. E. (2001). An eye movement study of insight problem solving. Memory and Cognition, 29, 1000–1009.

429

Koehnken, G., Milne, R., Memon, A. and Bull, R. (1999). The cognitive interview: A meta-analysis. Psychology, Crime, and Law, 5, 3–27. Koenigs, M., Young, L., Adolphs, R., Tranel, D., Cushman, F., Hauser, M. et al. (2007). Damage to the prefrontal cortex increases utilitarian moral judgments. Nature, 446, 908–911. Koffka, K. (1935). Principles of Gestalt Psychology. New York: Harcourt Brace. Köhler, W. (1925). The Mentality of Apes. New York: Harcourt Brace. Kolb, B. and Whishaw, I. Q. (1996). Fundamentals of Human Neuropsychology (4th edn). New York: Freeman. Kopelman, M. D. (1989). Remote and autobiographical memory, temporal context memory and frontal atrophy in Korsakoff and Alzheimer patients. Neuropsychologia, 27, 437–460. Kopelman, M. D. (1995). Assessment of psychogenic amnesias. In A. D. Baddeley, B. A. Wilson and F. N. Watts (eds) Handbook of Memory Disorders (1st edn, pp. 427–448). Chichester: Wiley. Kopelman, M. D. (2002). Psychogenic amnesia. In A. D. Baddeley, M. D. Kopelman and B. A. Wilson (eds) Handbook of Memory Disorders (2nd edn, pp. 451–472). Chichester: Wiley. Kopelman, M. D. (2010). Varieties of confabulation and delusion. Cognitive Neuropsychiatry, 15, 14–37. Kopelman, M. D., Wilson, B. A. and Baddeley, A. D. (1990). The Autobiographical Memory Interview. Bury St. Edmunds: Thames Valley Test Company. Kopelman, M. D., Stanhope, N. and Kingsley, D. (1999). Retrograde amnesia in patients with diencephalic, temporal lobe, or frontal lesions. Neuropsychologia, 35, 1533–1545. Kopelman, M. D., Lasserson, D., Kingsley, D., Bello, F., Rush, C. et al. (2001). Structural MRI volumetric analysis in patients with organic amnesia, 2: Correlations with anterograde memory and executive tests in 40 patients. Journal of Neurology, Neurosurgery, and Psychiatry, 71, 23–28. Koriat, A., Goldsmith, M. and Pansky, A. (2001). Towards a psychology of memory accuracy. Annual Review of Psychology, 481–537. Korsakoff, S. S. (1887). Troubles de l’activite psychique dans la paralysie alcoolique et leurs rapports avec les troubles de la sphere psychique dans la vevrite multiple d’origine non alcoolique. Vestnik Psychiatrii, 4, 2. Kousta, S. T., Vigliocco, G., Vinson, D. P., Andrews, M., Del Campo, E. (2011). The representation of

430

References

abstract words: Why emotion matters. Journal of Experimental Psychology: General, 140, 14–34. Kozak, K., Pohl, J., Birk, W., Greenberg, J., Artz, B., Bloomer, M., Cathey, L. and Curry, R. (2006). Evaluation of lane departure warnings for drowsy drivers. Proceedings of the Human Factors and Ergonomics Society, 2400–2404. Króliczak, G., Heard, P., Goodale, M. A. and Gregory, R. L. (2006). Dissociation of perception and action unmasked by the hollow-face illusion. Brain Research, 1080, 9–16. Kuffler, S. W. (1953). Discharge patterns and functional organisation of mammalian retina. Journal of Neurophysiology, 16, 37–68. Kuhl, B. A., Kahn, I., Dudukovich, N. M. and Wagner, N. M. (2008). Overcoming suppression in order to remember: Contributions from anterior cingulated and ventrolateral prefrontal cortex. Cognitive Affective and Behavioural Neuroscience, 8, 211–221. Külpe, O. (1895). The Outlines of Psychology: Based Upon the Results of Experimental Investigation. New York: Swan Sonnenschein and Co. Kurtz, K. J. and Loewenstein, J. (2007). Converging on a new role for analogy in problem solving and retrieval: When two problems are better than one. Memory and Cognition, 35, 334–341. Kussmaul, A. (1877). Die Storungen der Sprache. Leipzig: Vogel. LaBar, K. S. and Cabeza, R. (2006). Cognitive neuroscience of emotional memory. Nature Reviews Neuroscience, 7, 54–64. LaBar, K. S., Gitelman, D. R., Parrish, T. B. and Mesulam, M. (1999). Neuroanatomic overlap of working memory and spatial attention networks: a functional MRI comparison within subjects. Neuroimage, 10, 695–704. Laberge, D. (1983). Spatial extent of attention to letters and words. Journal of Experimental Psychology: Human Perception and Performance, 9, 371–379. Laird, J., Newell, A. and Rosenbloom, P. (1987). SOAR: An architecture for general intelligence. Artificial Intelligence, 33, 1–64. Lang, A. J., Craske, M. J. and Bjork, R. A. (1999). Implications of a new theory of disuse for the treatment of emotional disorders. Clinical Psychology; Science and Practice, 6, 80–94. Langham, M., Hole, G., Edwards, J. and O’Neil, C. (2002). An analysis of “looked but failed to see” accidents involving parked police vehicles. Ergonomics, 45(3), 167–185. Lashley, K. S. (1950). In search of the engram. Symposium of the Society of Experimental Biology, 4, 454–482.

Lavie, N. (1995). Perceptual load as a necessary condition for selective attention. Journal of Experimental Psychology; Human Perception and Performance, 21, 451–468. Lavie, N. (2005). Distracted and confused? Selective attention under load. Trends in Cognitive Science, 9, 75–82. Lavie, N. (2006). The role of perceptual load in visual awareness. Brain Research, 1080, 91–100. Lavie, N. (2010). Attention, distraction and cognitive control under load. Current Directions in Cognitive Science, 19(3), 143–148. Law, R., Groome, D., Thorn, L., Potts, R. and Buchanan, T. (2012). The relationship between retrieval-induced forgetting, anxiety, and personality. Anxiety, Stress and Coping, 25, 711–718. Lawson, I. R. (1962). Visual-spatial neglect in lesions of the right cerebral hemisphere: A study in recovery. Neurology, 12, 23–33. Leach, C. W. and Spears, R. (2008). “A vengefulness of the impotent”: The pain of in-group inferiority and schadenfreude toward successful outgroups. Journal of Personality and Social Psychology, 95, 1383–1396. Lederman, S. J. and Klatzky, R. L. (1990). Haptic classification of common objects: Knowledge-driven exploration. Cognitive Psychology, 22, 421–459. Lee, A. C. H., Bussey, T. J., Murray, E. A., Saksida, L. M., Epstein, R. A., Kapur, N., Hodges, J. R. and Graham, K. S. (2005). Perceptual deficits in amnesia: Challenging the medial temporal lobe mnemonic view. Neuropsychologia, 43, 1–11. Lee, A. C. H., Yeung, L-K. and Barense, M. D. (2012). The hippocampus and visual perception. Frontiers of Human Neuroscience, 6, 91. doi: 10.3389/fnhum.2012.00091. Legrenzi, P., Girotto, V. and Johnson-Laird, P. N. (2003). Models of consistency. Psychological Science, 14, 131–137. Lench, H. C. and Levine, L. J. (2005). Effects of fear on risk and control judgments and memory: Implications for health promotion messages. Cognition and Emotion, 19, 1049–1069. Lench, H. C. and Ditto, P. H. (2008). Automatic optimism: Biased use of base rate information for positive and negative events. Journal of Experimental Social Psychology, 44, 631–639. Lerner, J. S. and Keltner, D. (2001). Fear, anger, and risk. Journal of Personality and Social Psychology, 81, 146–159. Lerner, J. S. and Tiedens, L. Z. (2006). Portrait of the angry decision maker: How appraisal tendencies shape anger’s influence on cognition. Journal of Behavioral Decision Making, 19, 115–137.

References Lerner, J. S., Gonzalez, R. M., Small, D. A. and Fischhoff, B. (2003). Effects of fear and anger on perceived risks of terrorism: A national field experiment. Psychological Science, 14, 144–150. Levelt, W. J. M. (1989). Speaking: From Intention to Articulation. Cambridge, MA: MIT Press. Levelt, W. J. M. (1992). Accessing words in speech production: stages, processes and representations. Cognition, 42, 1–22. Levelt, W. (2012). A History of Psycholinguistics: The Pre-Chomskyan Era. Oxford: Oxford University Press. Levelt, W. J. M., Schriefers, H., Vorberg, D., Meyer, A. S., Pechmann, Th. and Havinga, J. (1991). The time course of lexical access in speech production: A study of picture naming. Psychological Review, 98, 122–142. Levelt, W. J. M., Roelofs, A. and Meyer, A. S. (1999). A theory of lexical access in speech production. Target Paper for Behavioral and Brain Sciences, 22, 1–75. Levine, B., Svoboda, E., Hay, J. F., Winocur, G. and Moscovitch, M. (2002). Ageing and autobiographical memory: Dissociating episodic from semantic retrieval. Psychology and Ageing, 17, 677–689. Levine, L. J. and Edelstein, R. S. (2009). Emotion and memory narrowing: A review and goal-relevance approach. Cognition and Emotion, 23, 833–875. Levy, J., Pashler, H. and Boer, E. (2006). Central interference in driving: Is there any stopping the psychological refractory period? Psychological Science, 17(3), 228–235. Lhermitte, F. (1983). “Utilization behaviour” and its relation to lesions of the frontal lobes. Brain, 106, 237–255. Lhermitte, F. (1986). Human autonomy and the frontal lobes. Part II: patient behaviour in complex and social situations: The “environmental dependency syndrome”. Annals of Neurology, 19, 335–343. Libet, B. (1985). Unconscious cerebral initiative and the role of conscious will in voluntary action. Behavioural and Brain Sciences, 8, 529–539. Lichtheim, L. (1885). On Aphasia. Brain, 7, 433–484. Liebenthal, E., Binder, J. R., Spitzer, S. M., Possing, E. T. and Medler, D. A. (2005). Neural substrates of phonemic perception. Cerebral Cortex, 15(10), 1621–31. Lief, H. and Fetkewicz, J. (1995). Retractors of false memories: The evolution of pseudomemories. The Journal of Psychiatry and Law, 23, 411–436.

431

Lien, M. C., Proctor, R. W. and Allen, P. A. (2002). Ideomotor compatibility in the psychological refractory period effect: 29 years of oversimplification. Journal of Experimental Psychology: Human Perception and Performance, 28, 396–409. Lindsay, P. H. and Norman, D. A. (1972). Human Information Processing. New York: Academic Press. Lindsay, D. S. and Read, J. D. (1994). Psychotherapy and memories of childhood sexual abuse: A cognitive perspective. Applied Cognitive Psychology, 8, 281–338. Linton, M. (1975). Memory for real-world events. In D. A. Norman and D. E. Rumelhart (eds) Explorations in Cognition. San Francisco: Freeman. Lisker, L. (1977). Factors in the maintenance and cessation of voicing. Phonetica, 34, 304–306. Lissauer, H. (1890). Ein Fall von Seelenblindheitnebt einem Beitrage zur Theorie Derselben. Archiv für Psychiatrie und Nervenkrankheit, 21, 222–270. Litvak, P. M., Lerner, J. S., Tiedens, L. Z. and Shonk, K. (2010). Fuel in the fire: How anger impacts judgment and decision-making. In M. Potegal, G. Stemmler and C. Spielberger (eds) International Handbook of Anger: Constituent and Concomitant Biological, Psychological, and Social Processes (pp. 287–310). New York: Springer. Liu, X., Crump, M. J. C. and Logan, G. D. (2010). Do you know where your fingers have been? Explicit knowledge of the spatial layout of the keyboard in skilled typists. Memory and Cognition, 38(4), 474–484. Local, J. and Kelly, J. (1986). Projection and silences: Notes on phonetic and conversational structure. Human Studies, 9, 185–204. Lockhart, R. S. and Craik, F. I. M. (1990). Levels of processing: A retrospective commentary on a framework for memory research. Canadian Journal of Psychology, 44, 87–112. Loeb, J. (1902). Comparative Physiology of the Brain and Comparative Psychology. New York: Putnam. Loewenstein, J., Thompson, L. and Gentner, D. (2003). Analogical learning in negotiation teams: Comparing cases promotes learning and transfer. Academy of Management Learning and Education, 2, 119–127. Loftus, E. L. and Palmer, J. C. (1974). Reconstruction of automobile destruction: An example of the interaction between language and memory. Journal of Verbal Learning and Verbal Behaviour, 13, 585–589.

432

References

Loftus, E. F. and Pickrell, J. E. (1995). The formation of false memories. Psychiatric Annals, 25, 720–725. Loftus, E. F. and Davis, D. (2006). Recovered memories. Annual Review of Clinical Psychology, 2, 469–498. Loftus, E. F., Loftus, G. R. and Messo, J. (1987). Some facts about “weapons focus”. Law and Human Behavior, 11, 55–62. Logan, G. D. and Crump, M. J. C. (2009). The left hand doesn’t know what the right hand is doing. Disruptive effects of attention to the hands while typewriting. Psychological Science, 20, 1296–1300. Logie, R. H. (1986). Visuo-spatial processes in working memory. Quarterly Journal of Experimental Psychology, 38A, 229–247. Logie, R. H. (1995). Visuo-Spatial Working Memory. Hove: Erlbaum. Logie, R. H. (2011). The functional organisation and capacity limits of working memory. Current Directions in Psychological Science, 20, 240– 245. Logie, R. H., Baddeley, A. D., Mane, A., Donchin, E. and Sheptak, R. (1989). Working memory and the analysis of a complex skill by secondary task methodology. Acta Psychologica, 71, 53–87. Logothesis, N. K. (1994). Physiological studies of motion inputs. In A. T. Smith (ed.) Visual Detection of Motion (pp. 177–216). London: Academic Press. Lorayne, H. and Lucas, J. (1974). The Memory Book. London: W. H. Allen. Lorian, C. N. and Grisham, J. R. (2011). Clinical implications of risk aversion: An online study of risk-avoidance and treatment utilisation in pathological anxiety. Journal of Anxiety Disorders, 25, 840–848. Loveday, C. and Conway, M. A. (2011). Using SenseCam with an amnesic patient: Accessing inaccessible everyday memories. Memory, 19, 697–704. Luce, P. A. and Pisoni, D. B. (1998). Recognizing spoken words: The neighborhood activation model. Ear Hear, 19(1), 1–36. Luchins, A. S. (1942). Mechanization in problem solving. Psychological Monographs, 54:6, Whole No. 248. Luria, A. R. (1966). Higher Cortical Functions in Man. London: Tavistock. Luria, A. R. (1973). The Working Brain: An Introduction to Neuropsychology. Harmondsworth: Penguin Books. McCall, W. V. (2004). Quality of life and function after electroconvulsive therapy. British Journal of Psychiatry, 185, 405–409.

McCarthy, G., Puce, A., Gore, J. and Allison, T. (1997). Face-specific processing in the human fusiform gyrus. Journal of Cognitive Neuroscience, 9, 605–610. McCarthy, R. A., Kopelman, M. D. and Warrington, E. K. (2005). Remembering and forgetting of semantic knowledge in amnesia: A 16-year followup investigation of RFR. Neuropsychologia, 43, 356–372. McClelland, J. L. and Patterson, K. (2002). Rules or connections in past-tense inflections: What does the evidence rule out? Trends in Cognitive Sciences, 6(11), 465–472. McClelland, J. L. and Rumelhart, D. E. (1986). Parallel Distributed Processing: Explorations in the Microstructure of Cognition (Vols 1 and 2). Cambridge, MA: MIT Press. McDaniel, M. A. and Fisher, R. P. (1991). Tests and test feedback as learning sources. Contemporary Educational Psychology, 16, 192–201. McDaniel, M. A., Roediger, H. L. III and McDermott, K. B. (2007). Generalising testenhanced learning from the laboratory to the classroom. Psychonomic Bulletin and Review, 14, 200–206. McGeoch, J. A. (1932). Forgetting and the law of disuse. Psychological Review, 39, 352–370. McGettigan, C., Warren, J. E., Eisner, F., Marshall, C. R., Shanmugalingam, P. and Scott, S. K. (2011). Neural correlates of sublexical processing in phonological working memory. Journal of Cognitive Neuroscience, 23(4), 961–77. McGinn, C. (1999). The Mysterious Flame: Conscious Minds in a Material World. New York: Basic Books. MacGregor, J. N., Ormerod, T. C. and Chronicle, E. P. (2001). Information processing and insight: A process model of performance on the nine-dot and related problems. Journal of Experimental Psychology: Learning, Memory, and Cognition, 27, 176–201. McIntosh, R. D., Rossetti, Y. and Milner, A. D. (2002). Prism adaptation improves chronic visual and haptic neglect: A single case study. Cortex, 38, 309–320. Macken, W. J. and Jones, D. M. (1995). Functional characteristics of the “inner voice” and the “inner ear”: Single or double agency? Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 436–448. MacLeod, C. M. (1998). Training on integrated versus separated stroop tasks: The progression of interference and facilitation. Memory and Cognition, 26, 201–211.

References MacLeod, M. D. (2002). Retrieval-induced forgetting in eyewitness memory: Forgetting as a consequence of remembering. Applied Cognitive Psychology, 16, 135–149. MacLeod, M. D. and Macrae, C. N. (2001). Gone today but here tomorrow: The transient nature of retrieval-induced forgetting. Psychological Science, 12, 148–152. MacLeod, M. D. and Saunders, J. (2005). The role of inhibitory control in the production of misinformation effects. Journal of Experimental Psychology: Learning, Memory and Cognition, 31, 964–979. McLeod, P. D. (1978). Does probe RT measure central processing demand? Quarterly Journal of Experimental Psychology, 30, 83–89. Macmillan, M. B. (1986). A wonderful journey through the skull and brains: The travels of Mr Gage’s tamping iron. Brain and Cognition, 5, 67–107. McNally, R. J. and Geraerts, E. (2009). A new solution to the recovered memory debate. Perspectives on Psychological Science, 4, 126–134. McNeil, J. E. and Warrington, E. K. (1993). Prosopagnosia: A face-specific disorder. Quarterly Journal of Experimental Psychology, 46A, 1–10. McQueen, J. M. (1998). Segmentation of continuous speech using phonotactics. Journal of Memory and Language, 39, 21–46. Macrae, C. N. and MacLeod, M. D. (1999). On recollections lost: When practice makes imperfect. Journal of Personality and Social Psychology, 77, 463–473. MacSweeney, M., Capek, C. M., Campbell, R. and Woll, B. (2008). The signing brain: the neurobiology of sign language. Trends in Cognitive Sciences, 12(11), 432–440. Maier, N. R. F. (1930). Reasoning in humans I: On direction. Journal of Comparative Psychology, 10, 115–143. Maier, N. R. F. (1931). Reasoning in humans II: The solution of a problem and its appearance in consciousness. Journal of Comparative Psychology, 12, 181–194. Mair, W. G. P., Warrington, E. K. and Weiskrantz, L. (1979). Memory disorders in Korsakoff’s psychosis: A neuropathological and neuropsychological investigation of two cases. Brain, 102, 749–783. Majerus, S., Poncelet, M., Elsen, B. and van der Linden, M. (2006). Exploring the relationship between new word learning and short-term memory for serial order recall, item recall, and

433

item recognition. European Journal of Cognitive Psychology, 18, 848–873. Malhotra, P. A., Parton, A. D., Greenwood, R. and Husain, M. (2006). Noradrenergic modulation of space exploration in visual neglect. Annals of Neurology, 59(1), 186–190. Mandler, G. (1972). Organization and recognition. In E. Tulving and W. Donaldson (eds) Organization of Memory. New York: Academic Press. Mandler, G. (1980). Recognising: The judgement of a previous occurrence. Psychological Review, 27, 252–271. Mandler, G. (1989). Memory: Conscious and unconscious. In P. R. Soloman, G. R. Goethals, C. M. Kelley and B. R. Stephens (eds) Memory: Interdisciplinary Approaches. New York: Springer-Verlag. Mandler, G. (2002). Organisation: What levels of processing are levels of. Memory, 10, 333–338. Mandler, G. (2008). Familiarity breeds attempts: A critical review of dual-process theories of recognition. Perspectives on Psychological Science, 3, 390–399. Mandler, G. (2011). From association to organisation. Psychological Science, 20, 232–235. Mandler, G. Pearlstone, Z. and Koopmans, H. S. (1969). Effects of organisation and semantic similarity on a recall and recognition task. Journal of Verbal Learning and Verbal Behaviour, 8, 410–423. Maner, J. K., Richey, J. A., Cromer, K., Mallott, M., Lejuez, C. W., Joiner, T. E. et al. (2007). Dispositional anxiety and risk-avoidant decisionmaking. Personality and Individual Differences, 42, 665–675. Manly, T., Robertson, I. H. and Verity, C. (1997). Developmental unilateral visual neglect: A single case study. Neurocase, 3(1), 19–29. Manly, T., Woldt, K., Watson, P. and Warburton, E. (2002). Is motor perseveration in unilateral neglect ‘driven’ by the presence of neglected left-sided stimuli? Neuropsychologia, 40(11), 1794–1803. Manly, T., Dobler, V. B., Dodds, C. M. and George, M. A. (2005). Rightward shift in spatial awareness with declining alertness. Neuropsychologia, 43(12), 1721–1728. Mantyla, T. (1986). Optimising cue effectiveness: Recall of 500 and 600 incidentally learned words. Journal of Experimental Psychology: Learning, Memory, and Cognition, 12, 66–71. Marcel, A. J. (1980). Conscious and preconscious recognition of polysemous words: Locating the selective effects of prior verbal context.

434

References

In R. S. Nickerson (ed.) Attention and Performance, VII, NJ. Erlbaum. Marcel, A. J. (1983). Conscious and unconscious perception: An approach to the relations between phenomenal experience and perceptual processes. Cognitive Psychology, 15, 238–300. Marr, D. (1982). Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. San Francisco: Freeman. Marr, D. and Nishihara, K. (1978). Representation and recognition of the spatial organisation of threedimensional shapes. Philosophical Transactions of the Royal Society, Series B, 269–294. Marshall, J. C. and Newcombe, F. (1966). Syntactic and semantic errors in paralexia. Neuropsychologia, 4, 169–176. Marshall, J. C. and Newcombe, F. (1973). Patterns of paralexia: A psycholinguistic approach. Journal of Psycholinguistic Research, 2, 175–199. Marshall, J. C. and Halligan, P. W. (1988). Blindsight and insight in visuo-spatial neglect. Nature, 336, 766–767. Marshall, J. C. and Halligan, P. W. (1993). Visuospatial neglect: A new copying test to assess perceptual parsing. Journal of Neurology, 240, 37–40. Marslen-Wilson, W. D. (1973). Linguistic structure and speech shadowing at very short latencies. Nature, 244 (5417), 522–523. Marslen-Wilson, W. D. (1975). Sentence perception as an interactive parallel process. Science, 189, 226–228. Marslen-Wilson, W. D. (1987). Functional parallelism in spoken word-recognition. Cognition, 25, 71–102. Marslen-Wilson, W. (ed.) (1989). Lexical Representation and Process. Cambridge, MA: MIT Press. Marslen-Wilson, W. D. and Zwisterlood, P. (1989). Accessing spoken words: The importance of word onsets. Journal of Experimental Psychology: Human Perception and Performance, 15(3), 576–585. Martin, E. A. and Kerns, J. G. (2011). The influence of positive mood on different aspects of cognitive control. Cognition and Emotion, 25, 265–279. Martin, R. C. (1993). Short-term memory and sentence processing: Evidence from neuropsychology. Memory and Cognition, 21, 176–183. Massie, D. L., Campbell, K. L. and Williams, A. F. (1995). Traffic Accident involvement rates by driver age and gender. Accident Analysis and Prevention, 27(1), 73–87.

Mattingley, J. B., Rich, A. N., Yelland, G. and Bradshaw, J. L. (2001). Unconscious priming eliminates automatic binding of colour and alphanumeric form in synaesthesia. Nature, 410, 580–582. Mattson, A. J., Levin, H. S. and Grafman, J. (2000). A case of prosopagnosia following moderate closed head injury with left hemisphere focal lesion. Cortex, 36(1), 125–137. Mattys, S. L., White, L. and Melhorn, J. F. (2005). Integration of multiple speech segmentation cues: A hierarchical framework. Journal of Experimental Psychology: General, 134, 477–500. Maurer, D. and Mondloch, C. J. (2006). The infant as synesthete? Attention and Performance, XXI, 449–471. Mayes, A. R. (2002). Does focal retrograde amnesia exist and if so, what causes it? Cortex, 38, 670–673. Meeter, M., Murre, J. M. and Janssen, S. M. (2005). Remembering the news: Modelling retention data from a study with 14,000 participants. Memory and Cognition, 33, 793–810. Meeter, M., Murre, J., Janssen, S., Birkenhager, T. and van den Broek, W. W. (2011). Retrograde amnesia after electroconvulsive therapy: A temporary effect? Journal of Affective Disorders, 132, 216–222. Melby-Lervåg, M. and Hulme, C. (2013). Is working memory training effective? A meta-analytic review. Developmental Psychology, 49 (2), 270– 291. Memon, A. and Wright, D. B. (1999). Eyewitness testimony and the Oklahoma bombing. The Psychologist, 12, 292–295. Memon, A., Zaragoza, M., Clifford, B. R. and Kidd, L. (2009). Inoculation or antidote? The effects of cognitive interview timing on false memory for forcibly fabricated events. Law and Human Behavior, 34,105–117. Mendez, M. F. and Benson, D. F. (1985). Atypical conduction aphasia: A disconnection syndrome. Archives of Neurology, 42(9), 886–891. Meredith, C. and Edworthy, J. (1994). Sources of confusion in intensive care unit alarms. In N. Stanton (ed.) Human Factors in Alarm Design (p. 238). London: Taylor & Francis. Mesulam, M. (1999). Spatial attention and neglect: parietal, frontal and cingulate contributions to the mental representation and attentional targeting of salient extrapersonal events. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences, 354(1387, 29 July), 1325–1346.

References Michel, F. and Andreewsky, E. (1983). Deep dysphasia: An analog of deep dyslexia in the auditory modality. Brain and Language, 18, 212–223. Middlebrooks, C. J. (1992). Narrow-Band Sound localisation Related to External Ear acoustics. Journal of the Acoustical Society of America, 92(5), 2607–2624. Milders, M. V., Berg, I. J. and Deelman, B. G. (1995). Four-year follow-up of a controlled memory training study in closed head injured patients. Neuropsychological Rehabilitation, 5, 223–238. Miller, E. (1977). Abnormal Ageing: The Psychology of Senile and Presenile Dementia. Chichester: Wiley. Miller, G. A. (1956). The magic number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–93. Miller, L. A. and Tippett, L. J. (1996). Effects of focal brain lesions on visual problem-solving. Neuropsychologia, 34, 387–398. Mills, C. B., Boteler, E. H. and Oliver, G. K. (1999). Digit synaesthesia: A case study using a stroop-type test. Cognitive Neuropsychology, 16, 181–91. Milne, R. and Bull, R. (2002). Back to basics: A componential analysis of the original cognitive interview mnemonics with three age groups. Applied Cognitive Psychology, 16, 743–753. Milne, R. and Bull, R. (2003). Does the cognitive interview help children to resist the effects of suggestive questioning? Legal and Criminological Psychology, 8, 21–38. Milner, A. D. and Goodale, M. A. (1995). The Visual Brain in Action. Oxford: Oxford University Press. Milner, A. D. and Goodale, M. A. (2006). The Visual Brain in Action (2nd edn). Oxford: Oxford University Press. Milner, A. D. and Goodale, M. A. (2008). Two visual systems re-viewed. Neuropsychologia, 46, 774–785. Milner, B. (1964). Some effects of frontal lobectomy in man. In J. M. Warren and K. Akert (eds) The Frontal Granular Cortex and Behavior. New York: McGraw-Hill. Milner, B. (1966). Amnesia following operation on the temporal lobes. In C. W. M. hitty and O. L. Zangwill (eds) Amnesia. London: Butterworth. Milner, B., Corkin, S. and Teuber, H. L. (1968). Further analysis of hippocampal amnesia – 14-year follow-up of H. M. Neuropsychologia, 6, 215–234.

435

Miranda, R. and Kihlstrom, J. F. (2005). Mood congruence in childhood and recent autobiographical memory. Cognition and Emotion, 19, 981–998. Misanin, J. R., Miller, R. R. and Lewis, D. J. (1968). Retrograde amnesia produced by electroconvulsive shock after reactivation of a consolidated memory trace. Science, 160, 554–555. Mitchell, D. B. (2006). Nonconscious priming after 17 years. Psychological Science, 17, 925–929. Miyake, A. and Friedman, N. P. (2012). The nature and organisation of individual differences in executive functions: Four general conclusions. Current Directions in Psychological Science, 2, 8–14. Miyake, A., Friedman, N. P., Emerson, M.J, Witzki, A. H., Howerter, A. and Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49–100. Mohr, J. P., Pessin, M. S., Finkelstein, S., Funkenstein, H. H., Duncan, G. W. and Davis, K. R. (1978). Broca aphasia: Pathologic and clinical. Neurology, 28, 311–324. Moors, A. and De Houwer, J. (2006). Automaticity: A theoretical and conceptual analysis. Psychological Bulletin, 132, 297–326. Moray, N. (1959). Attention in dichotic listening: Affective cues and the influence of instruction. Quarterly Journal of Experimental Psychology, 11, 56–60. Moretto, G., Ladavas, E., Mattioli, F. and Di Pellegrino, G. (2010). A psychphysiological investigation of moral judgment after ventromedial prefrontal damage. Journal of Cognitive Neuroscience, 22, 1888–1899. Morris, P. E., Gruneberg, M. M., Sykes, R. M. and Merrick, A. (1981). Football knowledge and the acquisition of new results. British Journal of Psychology, 72, 479–484. Morris, R. D. and Baddeley, A. D. (1988). Primary and working memory functioning in Alzheimertype dementia. Journal of Clinical and Experimental Neuropsychology, 10, 279–296. Morris, R. G., Ahmed, S., Syed, G. M. and Toone, B. K. (1993). Neural correlates of planning ability: Frontal lobe activation during the Tower of London test. Neuropsychologia, 31, 1367–1378. Morris, R. G., Bullmore, E. T., Baron-Cohen, S. and Gray, J. A. (2002). Functional magnetic resonance imaging of synesthesia: activation of V4/ V8 by spoken words. Nature Neuroscience, 5, 371–375.

436

References

Morrison, C. M. and Ellis, A. W. (1995). Roles of word frequency and age of acquisition in word naming and lexical decision. Journal of Experimental Psychology: Learning, Memory and Cognition, 21, 116–133. Morsella, E. and Miozzo, M. (2002). Evidence for a cascade model of lexical access in speech production. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 555–563. Mort, D. J., Malhotra, P., Mannan, S. K., Rorden, C., Pambakian, A., Kennard, C. and Husain, M. (2003). The anatomy of visual neglect. Brain, 126, 1986–1997. Mortimer, A. and Shepherd, E. (1999). Frames of mind: Schemata guiding cognition and conduct in the interviewing of suspected offenders. In A. Memon and R. Bull (eds) Handbook of the Psychology of Interviewing (pp. 293–315). Chichester: Wiley. Morton, J. (1969). The interaction of information in word recognition. Psychological Review, 76, 165–178. Morton, J. (1970). A functional model for memory. In D. A. Norman (ed.) Models of Human Memory. New York: Academic Press. Morton, J. (1979). Facilitation in word recognition: Experiments causing change in the Logogen model. In P. A. Kolers, M. E. Wrolstad and H. Bouma (eds) Processing of Visible Language. New York: Plenum. Morton, J. and Patterson, K. (1980). A new attempt at an interpretation, or, an attempt at a new interpretation. In M. Coltheart, K. E. Patterson, J. C. Marshall (eds) Deep Dyslexia (pp. 91–118). London: Routledge and Kegan Paul. Morton, J. and Patterson, K. (1987). A new attempt at an interpretation, or, an attempt at a new interpretation. In M. Coltheart, K. E. Patterson and J. C. Marshall (eds) Deep Dyslexia (2nd edn). London: Routledge. Moscovitch, M. (1989). Confabulation and the frontal system: strategic versus associative retrieval in neuropsychological theories of memory. In H. L. Roediger and F. I. M. Craik (eds) Variety of Memory and Consciousness: Essays in Honour of Endel Tulving. Hillsdale, NJ: Lawrence Erlbaum Associates. Moscovitch, M., Yaschyshyn, M., Ziegler, M. and Nadel, L. (1999). Remote episodic memory and retrograde amnesia: Was Endel Tulving right all along? In E. Tulving (ed.) Memory, Consciousness, and the Brain: The Tallin Conference. New York: Psychology Press.

Mulligan, N. W. and Picklesimer, M. (2012). Levels of processing and the cue-dependent nature of recollection. Journal of Memory and Language, 66, 79–92. Murty, V. P., Ritchey, M., Adcock, R. A. and LaBar, K. S. (2010). fMRI studies of successful emotional memory encoding: A quantitative metaanalysis. Neuropsychologia, 48, 3459–3469. Mustanski, B. (2007). The influence of state and trait affect on HIV risk behaviors: A daily diary study of MSM. Health Psychology, 26, 618–626. Muter, P. (1980). Very rapid forgetting. Memory and Cognition, 8, 174–179. Myles, K. M., Dixon, M. J., Smilek, D. and Merikle, P. M. (2003). Seeing double: The role of meaning in alphanumeric-colour synaesthesia. Brain and Cognition, 53, 342–345. Na, D. L., Adair, M. D., Kang, Y., Chung, C. S., Lee, K. H. and Heilman, K. M. (1999). Motor perseverative behaviour on a line cancellation task. Neurology, 52, 1569–1576. Nader, K., Schafe, G. and Ledoux, J. E. (2000). The labile nature of the consolidation theory. Nature Neuroscience Reviews, 1, 216–219. Naeser, M. A., Helm-Estabrooks, N., Haas, G., Auerbach, S. and Srinivasan, M. (1987). Relationship between lesion extent in “Wernicke’s area” on computed tomographic scan and predicting recovery of comprehension in Wernicke’s aphasia. Archives of Neurology, 44, 73–82. Nairne, J. S. (2002a). The myth of the encodingretrieval match. Memory, 10, 389–395. Nairne, J. S. (2002b). Remembering over the short term: The case against the standard model. Annual Review of Psychology, 53, 53–81. Naish, P. (2005). Attention. In N. Braisby and A. Gellatly (eds) Cognitive Psychology. Oxford: Oxford University Press. Nakamura, N., Fujita, K., Ushitani, T. and Miyata, H. (2006). Perception of the standard and the reversed Muller-Lyer figures in pigeons and humans. Journal of Comparative Psychology, 120(3), 252. Navarro, J., Mars, F. and Hoc, J.-M. (2007). Lateral control assistance for car drivers: A comparison of motor priming and warning systems. Human Factors, 49(5), 950–960. Navon, D. (1977). Forest before trees: The precedence of global features in visual perception. Cognitive Psychology, 9, 353–383. Neath, I. and Nairne, J. S. (1995). Word-length effects in immediate memory: Overwriting the trace decay theory. Psychonomic Bulletin and Review, 2, 429–441.

References Neisser, U. (1967). Cognitive Psychology. NewYork: Appleton-Century-Crofts. Neisser, U. (1976). Cognition and Reality. San Francisco: Freeman. Neisser, U. (1982). Memory Observed. San Francisco: Freeman. Neisser, U. (1994). Multiple systems: A new approach to cognitive theory. European Journal of Cognitive Psychology, 6(3), 225–241. Neisser, U. and Becklen, P. (1975). Selective looking: Attending to visually superimposed events. Cognitive Psychology, 7, 480–494. Neisser, U. and Harsch, N. (1992). Phantom flashbulbs: False connections of hearing the news about Challenger. In E. Winograd and U. Neisser (eds) Affect and Accuracy in Recall: Studies of “Flashbulb” Memories. New York: Cambridge University Press. Nelson, H. E. (1976). A modified card sorting test sensitive to frontal lobe defects. Cortex, 12, 313–324. Nelson, K. and Ross, G. (1980). The generalities and specifics of long-term memory in infants and younger children. In M. Perlmutter (ed.) Children’s Memory: New Directions for Child Development. San Francisco CA: Jossey-Bass. Neufeld, J., Sinke, C., Zedler, M., Dillo, W., Emrich, H. M., Bleich, S. and Szycik, G. R. (2012). Disinhibited feedback as a cause of synesthesia: Evidence from a functional connectivity study on auditory-visual synesthetes. Neuropsychologia, 50(7), 1471–1477. Newell, A. and Simon, H. A. (1961). Computer simulation of human thinking. Science, 134, 2011–2017. Newell, A. and Simon, H. A. (1972). Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall. Newell, A. and Rosenbloom, P. S. (1981). Mechanisms of skill acquisition and the law of practice. In J. R. Anderson (ed.) Cognitive Skills and Their Acqusition. Hillsdale, NJ; Lawrence Earlbaum Associates. Newell, A., Shaw, J. C. and Simon, H. A. (1958). Elements of a theory of human problem solving. Psychological Review, 65, 151–166. Newstead, S. E., Ellis, M. C., Evans, J. St. B. T. and Dennis, I. (1997). Conditional reasoning with realistic material. Thinking and Reasoning, 3, 49–76. Newstead, S. E., Handley, S. J., Harley, C., Wright, H. and Farrelly, D. (2004). Individual differencs in deductive reasoning. The Quarterly Journal of Experimental Psychology, 57A(1), 33–60.

437

Nieuwenstein, M. R., Potter, M. C. and Theeuwes, J. (2009). Unmasking the attentional blink. Journal of Experimental Psychology: Human Perception and Performance, 35(1), 159–169. Nilsson, L. G. and Gardiner, J. M. (1993). Identifying exceptions in a database of recognition failure studies from 1973 to 1992. Memory and Cognition, 21, 397–410. Norman, D. A. (1981). Categorization of action slips. Psychological Review, 88, 1–15. Norman, D. A. and Shallice, T. (1986). Attention to action: Willed and automatic control of behaviour. In R. Davison, G. Shwartz and D. Shapiro (eds) Consciousness and Self Regulation: Advances in Research and Theory. New York: Plenum. Norman, J. (2001). Ecological psychology and the two visual systems: Not to worry. Ecological Psychology, 13(2), 135–145. Norman, J. (2002). Two visual systems and two theories of perception: An attempt to reconcile the constructivist and ecological approaches. Behavioral and Brain Sciences, 25(1), 73–96. Nunn, J. A., Gregory, L. J., Brammer, M., Williams, S. C. R., Parslow, D. M. et al. (2002). Functional magnetic resonance imaging of synesthesia: Activation of V4/V8 by spoken words. Nature Neuroscience, 4, 371–375. Nyberg, L. (2002). Levels of processing: A view from functional brain imaging. Memory, 10, 345–348. Nys, G. M., van Zandvoort, M. J. E., Roks, G., Kappelle, L. J., de Kort, P. L. and de Haan, E. H. (2004). The role of executive functioning in spontaneous confabulation. Cognitive and Behavioural Neurology, 17, 213–218. Oaksford, M. (2005). Reasoning. In N. Braisby and A. Gellatly (eds) Cognitive Psychology. Oxford: Oxford University Press. Oaksford, M. and Chater, N. (1994). A rational analysis of the selection task as optimal data selection. Psychological Review, 101, 608–631. Oaksford, M. and Chater, N. (1998). Rationality in an Uncertain World: Essays on the Cognitive Science of Human Reasoning. Hove: Psychology Press. Oaksford, M. and Chater, N. (2001). The probabilistic approach to human reasoning. Trends in Cognitive Sciences, 5, 349–357. Oaksford, M. and Chater, N. (2007). Bayesian Rationality: The Probabilistic Approach to Human Reasoning. Oxford: Oxford University Press. Oaksford, M. and Chater, N. (2009). Precis of Bayesian rationality: The probabilistic approach

438

References

to human reasoning. Behavioral and Brain Sciences, 32, 69–84. Oaksford, M. and Chater, N. (2010). Conditional inferences and constraint satisfaction: Reconciling mental models and the probabilistic approach. In M. Oaksford and N. Chater (eds) Cognition and Conditionals: Probability and Logic in Human Thinking (pp. 309–334). Oxford: Oxford University Press. Oaksford, M., Morris, F., Grainger, B. and Williams, J. M. G. (1996). Mood, reasoning, and central executive processes. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 476–492. Oatley, K. and Johnson-Laird, P. N. (1987). Towards a cognitive theory of emotions. Cognition and Emotion, 1, 29–50. Oberauer, K. (2003). Understanding serial position curves in short-term recognition and recall. Journal of Memory and Language, 4, 469–483. Obleser, J., Boecker, H., Drzezga, A., Haslinger, B., Hennenlotter, A., Roettinger, M., Eulitz, C. and Rauschecker, J. P. (2006). Vowel sound extraction in anterior superior temporal cortex. Human Brain Mapping, 27(7), 562–571. Obleser, J., Wise, R. J., Dresner, M. and Scott, S. K. (2007). Functional integration across brain regions improves speech perception under adverse listening conditions. Journal of Neuroscience, 27(9), 2283–2289. O’Connor, M., Butters, N., Miliotis, P., Eslinger, P. and Cermak, L. S. (1992). The dissociation of retrograde and anterograde amnesia in a patient with Herpes Encephalitis. Journal of Clinical and Experimental Neuropsychology, 14, 159–178. Ogden, J. A. and Corkin, S. (1991). Memories of H. M. In W. C. Abraham, M. C. Corballis and K. G. White (eds) Memory Mechanisms: A Tribute to G. V. Goddard. Hillsdale, NJ: Erlbaum. Ohlsson, S. (1992). Information processing explanations of insight and related phenomena. In M. T. Keane and K. J. Gilhooly (eds) Advances in the Psychology of Thinking (pp. 1–44). London: Harvester Wheatsheaf. Oldfield, S. R. and Parker, S. P. A. (1984a). Acuity of sound localization: A topography of auditory space. I. Normal conditions. Perception, 13, 581–600. Oldfield, S. R. and Parker, S. P. A. (1984b). Acuity of sound localization: a topography of auditory space. II. Pinna cues absent. Perception, 13, 601–617. Olivers, C. N. L. (2007). The time course of attention: It is better than we thought. Current

Directions in Psychological Science, 16, 11–15. Öllinger, M., Jones. G. and Knoblich, G. (2006). Heuristics and representational change in twomove matchstick arithmetic tasks. Advances in Cognitive Psychology, 2, 239–253. Öllinger, M., Jones, G. and Knoblich, G. (2008). Investigating the effect of mental set on insight problem solving. Experimental Psychology, 55, 269–282. O’Regan, J. K. (1992). Solving the “real” mysteries of visual perception: The world as an outside memory. Canadian Journal of Psychology, 46(3), 461–488. Ormerod, T. C., MacGregor, J. N. and Chronicle, E. P. (2002). Dynamics and constraints in insight problem solving. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 791–799. O’Rourke, T. B. and Holcomb, P. J. (2002). Electrophysiological evidence for the efficiency of spoken word processing. Biological Psychology, 60(2–3), 121–150. Ost, J., Granhag, P., Udell, J. and Hjelmsater, E. R. (2008). Familiarity breeds distortion: The effects of media exposure on false reports concerning media coverage of the terrorist attacks in London on 7 July 2005. Memory, 16, 76–85. Otten, L. J. and Rugg, M. D. (2001). Taskdependency of the neural correlates of episodic encoding as measured by fMRI. Cerebral Cortex, 11, 1150–1160. Owen, A. M., Downes, J. J., Sahakian, B. J., Polkey, C. E. and Robbins, T. W. (1990). Planning and spatial working memory following frontal lobe lesions in man. Neuropsychologia, 28, 1021–1034. Owen, A. M., Roberts, A. C., Polkey, C. E., Sahakian, B. J. and Robbins, T. W. (1991). Extra-dimension versus intra-dimensional shifting performance following frontal lobe excisions, temporal lobe excisions or amygdalo-hippocampectomy in man. Neuropsychologia, 29, 993–1006. Owen, A. M., McMillan, K. M., Laird, A. R. and Bullmore, E. (2005). N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies. Human Brain Mapping, 25, 46–59. Owen, D. H. (1990). Lexicon of terms for the perception and control of self-motion and orientation. In R. Warren and A. H. Wertheim (eds) Perception and Control of Self-Motion (pp. 33–50). Hillsdale, NJ: Lawrence Erlbaum. Ozonoff, S., Strayer, D., McMahon, W. and Filoux, F. (1994). Executive function abilities in autism

References and Tourette syndrome: An information-processing approach. Journal of Child Psychology and Psychiatry, 35, 1015–1032. Oztekin, I., Davachi, L. and McElree, B. (2010). Are representations in working memory distinct from representations in long-term memory? Neural evidence in support of a single store. Psychological Science, 21, 1123–1133. Parkin, A. J. (1983). The relationship between orienting tasks and the structure of memory traces: Evidence from false recognition. British Journal of Psychology, 74, 61–69. Parkin, A. J. (1993). Memory: Phenomena, Experiment, and Theory. Oxford: Blackwell. Parkin, A. J. (1996). Explorations in Cognitive Neuropsychology. Oxford: Blackwell. Parkin, A. J. (1997). Memory and Amnesia. Oxford: Blackwell. Parkin, A. J. and Walter, B. (1992). Ageing, conscious recollection, and frontal lobe dysfunction. Psychology and Ageing, 7, 290–298. Parkin, A. J., Reid, T. and Russo, R. (1990). On the differential nature of implicit and explicit memory. Memory and Cognition, 18, 507–514. Parkin, A. J., Gardiner, J. M. and Rosser, R. (1995a). Functional aspects of recollective experience in face recognition. Consciousness and Cognition, 4, 387–398. Parkin, A. J., Walter, B. M. and Hunkin, N. M. (1995b). Relationships between normal ageing, frontal lobe function, and memory for temporal and spatial information. Neuropsychology, 9, 304–312. Parra, M. A., Abrahams, S., Fabi, K., Logie, R., Luzzi, S. and Della Sala, S. (2009). Short-term memory binding deficits in Alzheimer’s Disease. Brain, 132, 1057–1066. Parsons, L. M. and Osherson, D. (2001). New evidence for distinct right and left brain systems for deductive versus probabilistic reasoning. Cerebral Cortex, 11, 954–965. Pashler, H. (1990). Do response modality effects support multi-processor models of divided attention? Journal of Experimental Psychology: Human Perception and Performance, 16, 826–842. Pashler, H. (1994). Dual task interference in simple tasks: Data and Theory. Psychological Bulletin, 16, 220–224. Patterson, K. (1982). The relationship between reading and phonological coding: Further neuropsychological observations. In A. W. Ellis (ed.) Normality and Pathology in Cognitive Functions (pp. 77–111). London: Academic Press.

439

Patterson, K., Nestor, P. J., and Rogers, T. T. (2007). Where do you know what you know? The representation of semantic knowledge in the human brain. Nature Reviews Neuroscience, 8(12), 976–987. Pecher, C., Lemercier, C. and Cellier, J.-M. (2009). Emotions drive attention: Effects on driver’s behaviour. Safety Science, 47, 1254–1259. Peelen, M. V., Lucas, N., Mayer, E. and Vuilleumier, P. (2009). Emotional attention in acquired prosopagnosia. Scan, 4, 268–277. doi:10.1093/scan/ nsp014. Perret, E. (1974). The left frontal lobe of man and the suppression of habitual responses in verbal categorical behavior. Neuropsychologica, 12, 323–330. Perrett, D. I., Smith, P. A., Potter, D. D., Mistlin, A. J., Head, A. S., Milner, A. D., Jeeves, M. A., (1985). Visual cells in the temporal cortex sensitive to face view and gaze direction. Proceedings of the Royal Society B: Biological Sciences, 223, 293–317. Persaud, N., McLeod, P. and Cowie, A. (2007). Post-decision wagering objectively measures awareness. Nature Neuroscience, 10, 257–261. Peru, A. and Avesani, R. (2008). To know what it is for, but not how it is: semantic dissociations in a case of visual agnosia. Neurocase, 14(3), 249–63. doi:10.1080/13554790802269968. Peterson, L. R. and Peterson, M. J. (1959). Shortterm retention of individual items. Journal of Experimental Psychology, 58, 193–198. Phillips, C. E., Jarrold, C., Baddeley, A. D., Grant, J. and Karmiloff-Smith, A. (2004). Comprehension of spatial language terms in Williams syndrome: Evidence for an interaction between domains of strength and weakness. Cortex, 40, 85–101. Piercy, M. F. (1977). Experimental studies of the organic amnesic syndrome. In C. W. M. Whitty and O. L. Zangwill (eds) Amnesia. London: Butterworth. Pillemer, D. B. and White, S. H. (1989). Childhood events recalled by children and adults. In H. W. Reese (ed.) Advances in Child Development and Behaviour. San Diego CA: Academic Press. Pinker, S. (1991). Rules of language. Science, 253, 530–535. Pinker, S. (1997). How the Mind Works. London: Penguin. Pinker, S. (1999). Words and Rules. New York: Basic Books. Pinker, S. (2001). Four decades of rules and associations, or whatever happened to the past tense debate? In E. Dupoux (ed.) Language, the Brain,

440

References

and Cognitive Development: Papers in Honor of Jacques Mehler. Cambridge, MA: MIT Press. Plaut, D. C. and Shallice, T. (1993). Deep dyslexia: A case study of connectionist neuropsychology. Cognitive Neuropsychology, 10, 377–500. Poletiek, F. H. (1996). Paradoxes of falsification. The Quarterly Journal of Experimental Psychology, 49A, 447–462. Polivy, J. (1981). On the induction of emotion in the laboratory: Discrete moods or multiple affect states? Journal of Personality and Social Psychology, 41, 803–817. Poppel, E. Held, R. and Frost, D. (1973). Residual visual function after brain wounds involving the central visual pathways in man. Nature, 243, 295–296. Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 3–25. Posner, M. I. and Boies, S. J. (1971). Components of attention. Psychological Review, 78, 391–408. Posner, M. I. and Petersen, S. E. (1990). The attentional system of the human brain. Annual Review of Neuroscience, 13, 25–42. Posner, M. I. and Badgaiyan, R. D. (1998). Attention and neural networks. In R. W. Parks, D. S. Levine and R. D. Badgaiyan. Fundamentals of Neural Network Modelling. Cambridge, MA: MIT Press. Posner, M. I., Snyder, C. R. R. and Davidson, B. J. (1980). Attention and the detection of signals. Journal of Experimental Psychology: General, 109, 160–174. Potts, R., Law, R., Golding, J. and Groome, D. (2011). The reliability of retrieval-induced forgetting. European Psychologist, 1, 1–10. Power, M. J., Dalgleish, T., Claudio, V., Tata, P. and Kentish, J. (2000). The directed forgetting task: Application to emotionally valent material. Journal of Affective Disorders, 57, 147–157. Praamstra, P., Hagoort, P., Maassen, B. and Crul, T. (1991). Word deafness and auditory cortical function a case history and hypothesis. Brain, 114, 1197–1225. Price, C. J. and Devlin, J. T. (2003). The myth of the visual word form area. Neuroimage, 19(3), 473–81. Price, C. J., Wise, R. J., Warburton, E. A. et al. (1996). Hearing and saying: The functional neuro-anatomy of auditory word processing. Brain, 119, 919–931. Prince, S. E., Tsukiura, T. and Cabeza, R. (2007). Distinguishing the neural correlates of episodic memory encoding and semantic memory retrieval. Psychological Science, 18, 144–151.

Pujol, M. and Kopelman, M. D. (2003). Korsakoff’s syndrome. Advances in Clinical Neuroscience and Rehabilitation, 3, 14–17. Raghunathan, R. and Pham, M. T. (1999). All negative moods are not equal: Motivational influences of anxiety and sadness on decision making. Organizational Behavior and Human Decision Processes, 79, 56–77. Raine, A., Hulme, C., Chadderton, H. and Bailey, P. (1992). Verbal short-term memory span in speech-disordered children: Implications for articulatory coding in short-term memory. Child Development, 62, 415–423. Ramachandran, V. S. and Hubbard, E. M. (2002). Synaesthesia – a window into perception, thought and language. Journal of Consciousness Studies, 8, 3–34. Ranganath, C. (2010). Binding items and contexts: The cognitive neuroscience of episodic memory. Current Directions in Psychological Science, 19, 131–137. Rao, S. C., Rainer, G. and Miller, E. K. (1997). Integration of what and where in the primate prefrontal cortex. Science, 276, 821–824. Räsänen, M. and Summala, H. (1998). Attention and expectation problems in bicycle-car collisions: an in-depth study. Accident Analysis and Prevention, 30(5), 657–666. Rastle, K., Davis, M. H. and New, B. (2004). The broth in my brother’s brothel: Morphoorthographic segmentation in visual word recognition. Psychonomic Bulletin and Review, 11, 1090–1098. Rauschecker, J. P. and Scott, S. K. (2009). Maps and streams in the auditory cortex: nonhuman primates illuminate human speech processing. Nature Neuroscience, 12(6), 718–724. Raymond, J. E., Shapiro, K. and Arnell, K. M. (1992). Temporary suppression of visual processing in an RSVP task: An attentional blink? Journal of Experimental Psychology: Human Perception and Performance, 18, 653–662. Rayner, K. and Bertera, J. H. (1979). Reading without a fovea. Science, 206, 468–469. Read, J. and Bentall, R. (2010). The effectiveness of electroconvulsive therapy: A literature review. Epidemiologia e Psichiatria Sociale, 19, 333–346. Reason, J. T. (1979). Actions not as planned: The price of automatisation. In G. Underwood and R. Stevens (eds) Aspects of Consciousness: Vol. 1: Psychological Issues. London: Academic Press. Reed, J. M. and Squire, L. R. (1998). Retrograde amnesia for facts and events: Findings from four new cases. Journal of Neuroscience, 18, 3943–3954.

References Reed, L. J., Lasserson, D., Marsden, P., Stanhope, N., Stevens, T., Bello, F., Kingsley, D., Colchester, A. and Kopelman, M. D. (2003). FDG-PET findings in the Wernicke-Korsakoff syndrome. Cortex, 39, 1027–1045. Rees, G. (2007). Neural correlates of the contents of visual awareness in humans. Philosophical Transactions of the Royal Society B – Biological Sciences, 362, 877–886. Reeve, D. K. and Aggleton, J. P. (1998). On the specificity of expert knowledge about a soap opera: An everyday story of farming folk. Applied Cognitive Psychology, 12, 35–42. Regard, M. and Landis, T. (1984). Transient global amnesia: Neuropsychological dysfunction during attack and recovery of two “pure” cases. Journal of Neurology, Neurosurgery, and Psychiatry, 47, 668–672. Renault, B. S., Signoret, J., Debruille, B., Breton, F. and Bolgert, F. (1989). Brain potentials reveal covert facial recognition in prosopagnosia. Neuropsychologia, 27, 905–912. Reverberi, C., Lavaroni, A., Gigli, G. L., Skrap, M. and Shallice, T. (2005a). Specific impairments of rule induction in different frontal lobe subgroups. Neuropsychologia, 43, 460–472. Reverberi, C., Toraldo, A., D’Agostini, S. and Skrap, M. (2005b). Better without (lateral) frontal cortex? Insight problems solved by frontal patients. Brain, 128, 2882–2890. Reyna, V. F. and Brainerd, C. J. (2011). Dual processes in decision making and developmental neuroscience: A fuzzy-trace model. Developmental Review, 31, 180–206. Ribot, T. (1882). Diseases of Memory. New York: Appleton. Riccio, G. E. and McDonald, P. V. (1998). Multimodal Perception and Multicriterion Control of Nested Systems, 1, Coordination of Postural Control and Vehicular Control (Technical Report No. NASA/TP-3703): NASA. Richmond, J. and Nelson, C. A. (2007). Accounting for change in declarative memory: A cognitive neuroscience perspective. Developmental Review, 27, 349–373. Riddoch, M. J. and Humphreys, G. W. (1983). The effect of cueing on unilateral neglect. Neuropsychologia, 21, 589–599. Riddoch, M. J. and Humphreys, G. W. (1987). A case of integrative visual agnosia. Brain, 110, 1431–1462. Riddoch, M. J., Humphreys, G. W., Akhtar, N., Allen, H., Bracewell, R. M. and Schofield, A. J. (2008a). A tale of two agnosias: distinctions

441

between form and integrative agnosia. Cognitive Neuropsychology, 25(1), 56–92. doi:10.1080/ 02643290701848901. Riddoch, M. J., Johnston, R. A., Bracewell, R. M., Boutsen, L. and Humphreys, G. W. (2008b). Are faces special? A case of pure prosopagnosia. Cognitive Neuropsychology, 25(1), 3–26. doi:10.1080/02643290801920113. Robbins, T. W., Anderson, E. J., Barker, D. R., Bradley, A. C., Fearnyhough, C., Henson, R.,Hudson, S. R. and Baddeley, A. D. (1996). Working memory in chess. Memory and Cognition, 24, 83–93. Robertson, I. H. and Hawkins, K. (1999). Limb activation and unilateral neglect. Neurocase, 5, 153–160. Robertson, I. H., Manly, T., Beschin, N., Daini, R. et al. (1997). Auditory sustained attention is a marker of unilateral spatial neglect. Neuropsychologia, 35(12), 1527–1532. Robertson, I. H., Hogg, K. and McMillan, T. M. (1998a). Rehabilitation of unilateral neglect: improving function by contralesional limb activation. Neuropsychological Rehabilitation, 8(1), 19–29. Robertson, I. H., Mattingley, J. B., Rorden, C. and Driver, J. (1998b). Phasic alerting of neglect patients overcomes their spatial deficit in visual awareness. Nature, 395, 169–172. Robertson, I. H., McMillan, T. M., MacLeod, E., Edgeworth, J. and Brock, D. (2002). Rehabilitation by limb activation training reduces left-sided motor impairment in unilateral neglect patients: A single-blind randomised control trial. Neuropsychological Rehabilitation, 12(5), 439–454. Roca, M., Parr, A., Thompson, R., Woolgar, A., Torralva, T., Antoun, N., Manes, F. and Duncan, J. (2010). Executive function and fluid intelligence after frontal lobe lesions. Brain, 133, 234–247. Rock, I. (1977). In defense of unconscious inference. In W. Epstein (ed.) Stability and Constancy in Visual Perception: Mechanisms and Processes (pp. 321–377). New York: Wiley. Rock, I. (1983). The Logic of Perception. Cambridge, MA: MIT Press. Rogers, A., Pilgrim, D. and Lacey, R. (1993). Experiencing Psychiatry: Users Views of Services. London: MacMillan. Rogers, T. B., Kuiper, N. A. and Kirker, W. S. (1977). Self-reference and the encoding of personal information. Journal of Personality and Social Psychology, 35, 677–688.

442

References

Rose, D. (1996). Guest editorial: Some reflections on (or by?) grandmother cells. Perception, 25(8). Rose, N. S. and Craik, F. I. M. (2012). A processing approach to the working memory/long-term memory distinction: Evidence from the levels-ofprocessing span task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 1019–1029. Rosenbaum, R. S., Kohler, S., Schacter, D. L., Moscovitch, M., Westmacott, R., Black, S. E., Gao, F. and Tulving, E. (2005). The case of K. C.: Contributions of a memory-impaired person to memory. Neuropsychologia, 43, 989–1021. Rosenbaum, R. S., Gilboa, A., Levine, B., Winocur, G. and Moscovitch, M. (2009). Amnesia as an impairment of detail generation and binding: Evidence from personal, fictional, and semantic narratives in K. C. Neuropsychologia, 47, 2181–2187. Ross, E. D. (1980). Left medial parietal lobe and receptive language functions: Mixed transcortical aphasia after left anterior cerebral artery infarction. Neurology, 30, 144–151. Ross, E. D. (1981). The Aprosodias: Functionalanatomic organization of the affective components of language in the right hemisphere. Archives of Neurology, 38, 561–569. Ross, E. D. (2000). Affective prosody and the aprosodias. In M. M. Mesulam (ed.) Principles of Behavioral and Cognitive Neurology. New York: Oxford University Press. Ross, E. D. and Mesulam, M. M. (1979). Dominant language functions of the right hemisphere? Prosody and emotional gesturing. Archives of Neurology, 36, 144–148. Ross, E. D. and Monnot, M. (2008). Neurology of affective prosody and its functional-anatomic organization in right hemisphere. Brain and Language, 104(1), 51–74. Rossetti, Y., Rode, G., Pisella, L., Farne, A., Li, L., Boisson, D. and Perenin, M. T. (1998). Prism adaptation to a rightward optical deviation rehabilitates left hemispatial neglect. Nature, 395, 166–169. Rossi, S., Caverni, J. P. and Girotto, V. (2001). Hypothesis testing in a rule discovery problem: When a focused procedure is effective. The Quarterly Journal of Experimental Psychology, 54A, 263–267. Roth, H. L., Nadeau, S. E., Hollingsworth, A. L., Marie Cimino-Knight, A. and Heilman, K. M. (2006). Naming concepts: evidence of two routes. Neurocase, 12, 61–70. Rouw, R., Scholte, H. S. and Colizoli, O. (2011). Brain areas involved in synaesthesia: A

review. Journal of Neuropsychology, 5(2), 214–242. Rubenstein, H., Lewis, S. and Rubenstein, M. A. (1971). Evidence for phonemic recording in visual word recognition. Journal of Verbal Learning and Verbal Behavior, 10, 645–657. Rubin, D. C. and Wenzel, A. (1996). One hundred years of forgetting: A quantitative description of retention. Psychological Review, 103, 734–760. Rubin, D. C., Wetzler, S. E. and Nebes, R. D. (1986). Autobiographical memory across the life span. In D. C. Rubin (ed.) Autobiographical Memory. Cambridge: Cambridge University Press. Rubin, D. C., Rahhal, T. A. and Poon, L. W. (1998). Things learned in early adulthood are remembered best. Memory and Cognition, 26, 3–19. Rubin, E. (1915). Synoplevde Figurer. Copenhagen: Gyldendalske. Rueckert, L. and Grafman, J. (1996). Sustained attention deficits in patients with right frontal lesions. Neuropsychologia, 34, 953–963. Ruggeri, M., Guariglia, C. and Sabatini, U. (2009). Amnesia after right frontal subcortical lesion, following removal of a colloid cyst of the septum pellucidum and third ventricle. Minerva Psichiatrica, 50, 93–97. Rumelhart, D. E. and McClelland, J. L. (eds) (1986). Parallel-Distributed Processing: Explorations in the Microstructure of Cognition (Vol. 1). Cambridge, MA: MIT Press. Russell, W. R. (1971). The Traumatic Amnesias. London: Oxford University Press. Rusting, C. L. and DeHart, T. (2000). Retrieving positive memories to regulate negative mood: Consequences for mood-congruent memory. Journal of Personality and Social Psychology, 78, 737–752. Sabey, B. and Staughton, G. C. (1975). “Interacting roles of road environment, vehicle and road user.” Paper presented at the 5th International Conference of the International Association for Accident Traffic Medicine, London. Sacks, H., Schegloff, E. A. and Jefferson, G. (1974). A simplest systematics for the organization of turntaking for conversation. Language, 50, 696–735. Saffran, E. M., Bogyo, L. C., Schwartz, M. F. and Marin, O. S. M. (1987). Does deep dyslexia reflect right hemisphere reading? In M. Coltheart, K. E. Patterson and J. C. Marshall (eds) Deep Dyslexia (2nd edn). London: Routledge and Kegan Paul. Saffran, J. (2003). Statistical language learning: Mechanisms and constraints. Current Directions in Psychological Science, 12(4), 110–114.

References Salame, P. and Baddeley, A. D. (1982). Disruption of short-term memory by unattended speech: Implications for the structure of working memory. Journal of Verbal Learning and Verbal Behaviour, 21, 150–164. Saliba, A. (2001). Auditory-Visual Integration in Sound Localisation. University of Essex, Colchester. Saling, L. L. and Phillips, J. G. (2007). Automatic behaviour: Efficient not mindless. Brain Research Bulletin, 73, 1–20. Salmaso, D. and Denes, G. (1982). The frontal lobes on an attention task: A signal detection analysis. Pereptual and Motor Skills, 45, 1147–1152. Salthouse, T. A. (1994). Ageing associations: influence of speed on adult age differences in associative learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 1486–1503. Salthouse, T. A. (2011). Effects of age on timedependent cognitive change. Psychological Science, 22, 682–688. Samuelsson, H., Hjelmquist, E., Jensen, C., Ekholm, S. and Blomstrand, C. (1998). Nonlateralized attentional deficits: An important component behind persisting visuospatial neglect? Journal of Clinical and Experimental Neuropsychology, 20(1), 73–88. Sander, D. (2009). Amygdala. In D. Sander and K. R. Scherer (eds) The Oxford Companion to Emotion and the Affective Sciences (pp. 28–32). Oxford: Oxford University Press. Sarinopoulos, I., Grupe, D. W., Mackiewicz, K. L., Herrington, J. D., Lor, N., Steege, E. E. et al. (2010). Uncertainty during anticipation modulates neural responses to aversion in human insula and amygdala. Cerebral Cortex, 20, 929–940. Sayer, T. B., Sayer, J. R. and Devonshire, J. M. H. (2005). Assessment of a driver interface for lateral drift and curve speed warning systems: mixed results for auditory and haptic warnings. Proceedings of the Driving Assessment 2005: 3rd International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design (pp. 218–224). Schacter, D. L., Harbluk, J. L. and McLachlan, D. R. (1984). Retrieval without recollection: An experimental analysis of source amnesia. Journal of Verbal Learning and Verbal Behaviour, 23, 593–611. Schachter, D. L., Savage, C. and Rauch, S. (1996). Conscious recollection and the

443

human hippocampal formation: Evidence from PET. Proceedings of the National Academy of Sciences, 93, 321–325. Schacter, D. L., Wagner, A. D. and Buckner, R. L. (2000). Memory systems of 1999. In E. Tulving and F. I. M. Craik (eds) The Oxford Handbook of Memory. New York: Oxford University Press. Schaeken, W., Vandierendonck, A. Schroyens, W. and D’Ydewalle, G. (2007). The Mental Models Theory of Reasoning: Refinements and Extensions. Mahwah, NJ: Lawrence Erlbaum. Schank, R. C. and Abelson, R. P. (1977). Scripts, Plans, Goals, and Understanding. Hillsdale, NJ: Lawrence Erlbaum Associates. Scheerer, M. (1963). Problem solving. Scientific American, 208, 118–128. Schenk, T., Franz, V. and Bruno, N. (2011). Visionfor-perception and vision-for-action: Which model is compatible with the available psychophysical and neuropsychological data? Vision Research, 51(8), 812–818. Schiller, D., Monfils, M. H., Raio, C. M., Johnson, D. C., Ledoux, J. E. and Phelps, E. A. (2010). Preventing the return of fear in humans using reconsolidation update mechanisms. Nature, 463, 49–53. Schindler, B. A., Ramchandani, D., Matthews, M. K. and Podell, K. (1995). Competency and the frontal lobe. Psychosomatics, 36, 400–404. Schindler, I., Kerkhoff, G., Karnath, H.-O., Keller, I. and Goldenberg, G. (2002). Neck muscle vibration induces lasting recovery in spatial neglect. Journal of Neurology Neurosurgery and Psychiatry, 73, 412–419. Schlesinger, I. M. (1995). Cognitive Space and Linguistic Case: Semantic and Syntactic Categories in English. Cambridge: Cambrige University Press. Schmida, M., De Nunzioa, A. M. and Schieppatia, M. (2005). Trunk muscle proprioceptive input assists steering of locomotion. Neuroscience Letters, 384, 127–132. Schneider, G. E. (1967). Contrasting visuomotor functions of tectum and cortex in the golden hamster. Psychologische Forschung, 31, 52–62. Schneider, G. E. (1969). Two visual systems. Science, 163, 895–902. Schneider, W. X. and Deubel, H. (2002). Selection for perception and selection for spatial motor action are coupled in visual attention: A review of recent findings and new evidence from stimulus driven saccade control. In W. Printz and B. Hommel (eds) Attention and Performance XIX: Common

444

References

Mechanisms in Perception and Action. Oxford: Oxford University Press. Schneider, W. and Shiffrin, R. M. (1977). Controlled and automatic human information processing: 1. Detection, search, and attention. Psychological Review, 84, 1–66. Schnur, T. T., Schwartz, M. F., Kimberg, D. Y., Hirshorn, E., Coslett, H. B. and ThompsonSchill, S. L. (2009). Localizing interference during naming: Convergent neuroimaging and neuropsychological evidence for the function of Broca’s area. Proceedings of the National Academy of Sciences of the USA, 106(1), 322–327. doi: 10.1073/pnas.0805874106. Epub 2008 Dec 31. Schott, B. H., Henson, R. N. A., RichardsonKlavehn, A., Becker, C., Thoma, V. et al. (2005). Redefining implicit and explicit memory: The functional neuroanatomy of priming, remembering, and control of retrieval. Proceedings of the National Academy of Sciences of the USA, 102, 36–71. Schroyens, W. and Schaeken, W. (2003). A critique of Oaksford, Chater, and Larkin’s (2000). Conditional Probability Model of Conditional Reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 140–149. Schulz, K. P., Fan, J., Tang, C. Y., Newcorn, J. H., Buchsbaum, M. S. Cheung, A. M. and Halperin, J. M. (2004). Response inhibition in adolescents diagnosed with attention deficit hyperactivity disorder during childhood: An event-related FMRI study. American Journal of Psychiatry, 161, 1650–1657. Schwarz, N. (2000). Emotion, cognition, and decision making. Cognition and Emotion, 14, 433–440. Scotko, B. G., Kensinger, E. A., Locascio, J. J., Einstein, G., Rubin, D. C., Tupler, L. A., Krendl, A. and Corkin, S. (2004). Puzzling thoughts for H. M.: Can new semantic information be anchored in old semantic memories? Neuropsychology, 18, 756–769. Scott, J. J. and Gray, R. (2008). A comparison of tactile, visual, and auditory warnings for rear-end collision prevention in simulated driving. Human Factors: The Journal of the Human Factors and Ergonomics Society, 50(2), 264–275. Scott, S. K., Blank, S. C., Rosen, S. and Wise, R. J. S. (2000). Identification of a pathway for intelligible speech in the left temporal lobe. Brain, 123, 2400–2406. Scoville, W. B. and Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions.

Journal of Neurology, Neurosurgery, and Psychiatry, 20, 11–21. Sedda, A., Monaco, S., Bottini, G. and Goodale, M. A. (2011). Integration of visual and auditory information for hand actions: Preliminary evidence for the contribution of natural sounds to grasping. Experimental Brain Research, 209(3), 365–374. Segall, M. H., Campbell, D. T. and Herskovits, M. J. (1963). Cultural differences in the perception of geometrical illusions. Science, 139, 769–771. Sehm, B., Frisch, S., Thone-Otto, A., Horstman, A., Villringer, A., Obrig, H., de Beeck, H. P. (2011). Focal retrograde amnesis: Voxel-based morphometry findings in a case without MRI lesions. PLoS ONE, 6, doi: 10.1371journal.pone. 0026538. Seidenberg, M. (2012). Computational models of reading. In M. J. Spivey, K. McRae and M. Joanisse (eds) Cambridge Handbook of Psycholinguistics. Cambridge University Press. Seidenberg, M. S. and McClelland, J. L. (1989). A distributed, developmental model of word recognition and naming. Psychological Review, 96 (4), 523–568. Selfridge, O. G. (1959). Pandemonium: A paradigm for learning. In Symposium on the Mechanisation of Thought Processes. London: HMSO. Selfridge, O. G. and Neisser, U. (1960). Pattern recognition by machine. Scientific American, 203, 60–68. Seligman, M. E. P., Railton, P., Baumeister, R. F. and Sripada, C. (2013). Navigating into the future or driven by the past. Perspectives on Psychological Science, 8, 119–141. Sellal, F., Manning, L., Seegmuller, C., Scheiber, C. and Schoenfelder, P. (2002). Pure retrograde amnesia following a mild head trauma: A neuropsychological and metabolic study. Cortex, 38, 499–509. Sergent, J. and Signoret, J. L. (1992). Varieties of functional deficits in prosopagnosia. Cerebral Cortex, 2, 375–388. Service, E. (1992). Phonology, working memory, and foreign language learning. Quarterly Journal of Experimental Psychology, 45A, 21–50. Shaffer, L. H. (1975). Multiple attention in continuous verbal tasks. In P. M. A. Rabbitt and S. Dornic (eds) Attention and Performance V (pp. 157–167). New York: Academic Press. Shallice, T. (1982). Specific impairments of planning. Philosophical Transactions of the Royal Society of London, B298, 199–209.

References Shallice, T. (1988). From Neuropsychology to Mental Structure. Cambridge: Cambridge University Press. Shallice, T. and Warrington, E. K. (1974). The dissociation between long-term retention of meaningful sounds and verbal material. Neuropsychologia, 12, 553–555. Shallice, T. and Evans, M. E. (1978). The involvement of frontal lobes in cognitive estimation. Cortex, 13, 294–303. Shallice, T. and Warrington, E. K. (1980). Single and multiple component central dyslexic syndromes. In M. Coltheart, K. E. Patterson and J. C. Marshall (eds) Deep Dyslexia (pp. 119– 145). London: Routledge. Shallice, T. and Burgess, P. W. (1991a). Deficits in strategy application following frontal lobe damage in man. Brain, 114, 727–741. Shallice, T. and Burgess, P. W. (1991b). Higherorder cognitive impairments and frontal lobe lesions. In H. S. Levin, H. M. Eisenberg and A. L. Benton (eds) Frontal Lobe Function and Dysfunction. Oxford: Oxford University Press. Shallice, T., Burgess, P. W., Schon, F. and Baxter, D. M. (1989). The origins of utilization behaviour. Brain, 112, 1587–1598. Shapiro, K. L., Raymond, J. and Arnell, K. (2009). Attentional blink. Scholarpedia, 4(6), 3320. Retrieved from http://www.scholarpedia.org/w/ index.php?title=Attentional_blink&action= cite&rev=91007. Shapley, R. (1995). Parallel neural pathways and visual function. In M. S. Gazzaniga (ed.) The Cognitive Neurosciences (pp. 315–324). Cambridge, MA: MIT Press. Shaw, J. S., Bjork, R. A. and Handal, A. (1995). Retrieval-induced forgetting in an eyewitnessmemory paradigm. Psychonomic Bulletin and Review, 2, 249–253. Shepard, R. N. and Metzler, J. (1971). Mental rotation of three-dimensional objects. Science, 171, 701–703. Sheppard, D. M., Bradshaw, J. L., Mattingley, J. B. and Lee, P. (1999). Effects of stimulant medication on the lateralisation of line bisection judgements of children with attention deficit hyperactivity disorder. Journal of Neurology, Neurosurgery and Psychiatry, 66(1), 57–63. Shiffrin, R. M. and Schneider,W. (1977). Controlled and automatic information processing: II. Perception, learning, automatic attending and a general theory. Psychological Review, 84, 127–190.

445

Shimamura, A. P., Jernigan, T. L. and Squire, L. R. (1988). Korsakoff’s syndrome: Radiological (CT) findings and neuropsychological correlates. Journal of Neuroscience, 8, 4400–4410. Shimamura, A. P., Janowsky, J. and Squire, L. R. (1990). Memory for temporal order of events in patients with frontal lobe lesions and amnesic patients. Neuropsychologia, 28, 803–813. Shiv, B., Loewenstein, G., Bechera, A., Damasio, H. and Damasio, A. R. (2005). Investment behaviour and the negative side of emotion. Psychological Science, 16, 435–439. Siebert, M., Markowitsch, H. J. and Bartel, P. (2003). Amygdala, affect and cognition: Evidence from 10 patients with Urbach-Wiethe disease. Brain, 126, 2627–2637. Sierra, M. and Berrios, G. E. (2000). Flashbulb and flashback memories. In G. E. Berrios and J. R. Hodges (eds) Memory Disorders in Psychiatric Practice. New York: Cambridge University Press. Simcock, G. and Hayne, H. (2003). Age-related changes in verbal and non-verbal memory during early childhood. Developmental Psychology, 39, 805–814. Simon, H. A. and Reed, S. K. (1976). Modelling strategy shifts on a problem solving task. Cognitive Psychology, 8, 86–97. Simon, S. R., Khateb, A., Darque, A., Lazeyras, F., Mayer, E. and Pegna, A. J. (2011). When the brain remembers but the patient doesn’t: Converging fMRI and EEG evidence for covert recognition in a case of prosopagnosia. Cortex, 47, 825–838. Simons, J. S., Graham, K. S., Galton, C. J., Patterson, K. and Hodges, J. R. (2001). Semantic knowledge and episodic memory for faces in semantic dementia. Neuropsychology, 15, 101–114. Simons, J. S., Peers, P. V., Hwang, D. Y., Ally, B. A., Fletcher, P. C. and Budson, A. E. (2008). Is the parietal lobe necessary for recollection in humans? Neuropsychologia, 46, 1185–1191. Singh-Curry, V. and Husain, M. (2009). The functional role of the inferior parietal lobe in the dorsal and ventral stream dichotomy. Neuropsychologia, 47(6), 1434–1448. Skinner, B. F. (1938). The Behaviour of Organisms. New York: Appleton-Century-Crofts. Slobin, D. I. (1966). Grammatical transformations and sentence comprehension in childhood and adulthood. Journal of Verbal Learning and Verbal Behaviour, 5, 219–227. Small, D. A. and Lerner, J. S. (2008). Emotional policy: Personal sadness and anger shape judgments

446

References

about a welfare case. Political Psychology, 29, 149–168. Smilek, D., Dixon, M. J. and Merikle, P. M. (2005). Synaesthesia: Discordant male monozygotic twins. Neurocase, 11, 363–370. Smith, C., Frascino, J., Kripke, D., McHugh, P., Treisman, G. and Squire, L. (2010). Losing memories overnight: A unique form of human amnesia. Neuropsychologia, 48, 2833–2840. Smith, E. E. and Jonides, J. (1999). Working memory: A view from neuroimaging. Cognitive Psychology, 33, 5–42. Smith, E. E., Jonides, J. and Koeppe, R. A. (1996). Dissociating verbal and spatial working memory using PET. Cerebral Cortex, 6, 11–20. Smith, M. L. and Milner, B. (1984). Differential effects of frontal-lobe lesions on cognitive estimation and spatial memory. Neuropsychologia, 19, 781–793. Smith, M. L. and Milner, B. (1988). Estimation of frequency of occurrence of abstract designs after frontal or temporal lobectomy. Neuropsychologia, 26, 297–306. Smith, S. M. (1986). Environmental contextdependent memory: Recognition memory using a short-term memory task for input. Memory and Cognition, 14, 347–354. Smith, S. M. and Vela, E. (2001). Environmental context-dependent memory: A review and metaanalysis. Psychonomic Bulletin and Review, 8, 203–220. Snowling, M. (1998). Dyslexia as a phonological deficit: Evidence and implications. Child Psychology and Psychiatry Review, 3(1), 4–11. Song, Z., Wixted, J. T., Hopkins, R. O. and Squire, L. R. (2011). Impaired capacity for familiarity after hippocampal damage. Proceedings of the National Academy of Sciences of the United States of America, 108, 9655–9660. Soon, C. S., Brass, M., Heinze, H. J. and Hayes, J. D. (2008). Unconscious determinants of free decisions in the human brain. Nature Neuroscience, 10, 257–261. Sorger, B., Goebel, R., Schiltz, C. and Rossion, B. (2007). Understanding the functional neuroanatomy of acquired prosopagnosia. Neuroimage, 35(2), 836–852. Spence, C. (2010). Cross modal spatial attention. Annals of the New York Academy of Sciences, 1191, 182–200. Spence, C. and Driver, J. (1996). Audiovisual links in covert spatial attention. Journal of Experimental Psychology: Human Perception and Performance, 22, 1005–1030.

Spence, C. and Read, L. (2003). Speech shadowing while driving: On the difficulty of splitting attention between eye and ear. Psychological Science, 14, 251–256. Sperber, D. and Wilson, D. (1986). Relevance: Communication and Cognition. Oxford: Blackwell. (2nd edn 1995.) Sperling, G. (1960). The information available in brief visual presentations. Psychological Monographs, 74, 1–29. Spieler, D. H. and Balota, D. A. (1997). Bringing computational models of word naming down to the item level. Psychological Science, 8, 411–416. Spiers, H. J., Maguire, E. A. and Burgess, N. (2001). Hippocampal amnesia. Neurocase, 7, 357–382. Spitsyna, G., Warren, J. E., Scott, S. K., Turkheimer, F. E. and Wise, R. J. (2006). Converging language streams in the human temporal lobe. Journal of Neuroscience, 12, 26(28), 7328–7336. Sprague, J. M. (1966). Interaction of cortex and superior colliculus in mediation of visually guided behaviour in the cat. Science, 153, 1544–1547. Squeri, V., Sciutti,A., Gori, M., Masia, L., Sandini,G. and Konczak, J. (2012). Two hands, one perception: How bimanual haptic information is combined by the brain. Journal of Neurophysiology, 107(2), 544–550. Squire, L. R. (1982). Comparisons between forms of amnesia: Some deficits are unique to Korsakoff’s syndrome. Journal of Experimental Psychology: Learning, Memory and Cognition, 8, 560–571. Squire, L. R. (1992). Declarative and nondeclarative memory: Multiple brain systems supporting learning and memory. Journal of Cognitive Neuroscience, 4, 232–243. Squire, L. R., Slater, P. C. and Miller, P. L. (1981). Retrograde amnesia and bilateral electroconvulsive therapy. Archives of General Psychiatry, 38, 89–95. Squire, L. R., Cohen, N. J. and Nadel, L. (1984). The medial temporal region and memory consolidation: A new hypothesis. In H. Weingartner and E. Parker (eds) Memory Consolidation. Hillsdale, NJ: Erlbaum. Squire, L. R., Ojeman, J. G., Miezin, F. M., Petersen, S. E., Videen, T. O. and Raichle, M. E. (1992). Activation of the hippocampus in normal humans: A functional anatomical study of memory. Proceedings of the National Academy of Sciences of the USA, 89, 1837–1841. St Jaques, P. L. and Schacter, D. L. (2013). Modifying memory: Selectively enhancing and updating memories for a museum tour by reactivating them. Psychological Science, published online, doi: 10.1177/0956797612457377.

References Stanovich, K. E. and West, R. F. (2000). Individual differences in reasoning: Implications for the rationality debate? Behavioural and Brain Sciences, 23, 654–664. Starcke, K., Wolf, O. T., Markowitsch, H. J. and Brand, M. (2008). Anticipatory stress influences decision making under explicit risk conditions. Behavioral Neuroscience, 122, 1352–1360. Starcke, K., Pawlikowski, M., Wolf, O., AltstotterGleich, C. and Brand, M. (2011). Decision making under risk conditions is susceptible to interference by a secondary executive task. Cognitive Processing, 12, 177–182. Starr, A. and Phillips, L. (1970). Verbal and motor memory in the amnestic syndrome. Neuropsychologia, 8, 75–88. Stefanacci, L., Buffalo, E. A., Schmolk, H. and Squire, L. R. (2001). Profound amnesia after damage to the medial temporal lobe: A neuroanatomical and neuropsychological profile of patient E. P. Journal of Neuroscience, 20, 7024–7036. Steinvorth, S., Levine, B. and Corkin, S. (2005). Medial temporal lobe structures are needed to re-experience remote autobiographical memories: Evidence from H. M. and W. R. Neuropsychologia, 43, 479–496. Steven, M. S. and Blakemore, C. (2004). Visual synaesthesia in the blind. Perception, 33, 855–868. Stevenson, R. J. and Over, D. E. (2001). Reasoning from uncertain premises: effects of expertise and conversational context. Thinking and Reasoning, 7, 367–390. Stewart, F., Parkin, A. J. and Hunkin, N. M. (1992). Naming impairments following recovery from Herpes Simplex Encephalitis: Category specific? The Quarterly Journal of Experimental Psychology, 44A, 261–284. Stone, S. P., Halligan, P. W. and Greenwood, R. J. (1993). The incidence of neglect phenomena and related disorders in patients with an acute right or left-hemisphere stroke. Age and Ageing, 22(1), 46–52. Storandt, M. (2008). Cognitive deficits in the early stages of Alzheimer’s disease. Current Directions in Psychological Science, 17, 198–202. Storm, B. C. (2011). The benefit of forgetting in thinking and remembering. Current Directions in Psychological Science, 20, 291–295. Storm, B. C. and White, H. A. (2010). ADHD and retrieval-induced forgetting: Evidence for a deficit in inhibitory control of memory. Memory, 18, 265–271.

447

Strayer, D. L. and Drews, F. A. (2007). Cell-phone induced driver distraction. Current Directions in Psychological Science, 16, 128–131. Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643–662. Stuss, D. T. (2006). Frontal lobes and attention: Processes and networks, fractionation and integration. Journal of the International Neuropsychological Society, 12, 261–271. Stuss, D. T. and Alexander, M. P. (2000). Executive functions and the frontal lobes: A conceptual view. Psychological Research, 63, 289–298. Stuss, D. T. and Alexander, M. P. (2007). Is there a dysexecutive syndrome? Philosophical Transactions: Biological Sciences, 362, 901–915. Stuss, D. T., Floden, D., Alexander, M. P., Levine, B. and Katz, D. (2001). Stroop performance in focal lesion patients: dissociation of processes and frontal lobe lesion location. Neuropsychologia, 39, 771–786. Styles, E. A. (1997). The Psychology of Attention. Hove: Psychology Press. Suprenant, A. M. and Neath, I. (2009). The 9 lives of short-term memory. In A. Thorn and M. Page (eds) Interactions Between Short-Term and Long-Term Memory in the Verbal Domain (pp. 16–43). Hove: Psychology Press. Suslow, T., Konrad, C., Kugel, H., Rumstadt, D., Zwitserlood, P., Schöning, S. et al. (2010). Automatic mood-congruent amygdala responses to masked facial expressions in major depression. Biological Psychiatry, 67, 255–160. Talarico, J. M. and Rubin, D. C. (2003). Confidence, not consistency, characterises flashbulb memories. Psychological Science, 14, 455–461. Talarico, J. M. and Rubin, D. C. (2009). Flashbulb memories result from ordinary memory processes and extraordinary event characteristics. In O. Luminet and A. Curci (eds) Flashbulb Memories: New Issues and Perspectives. Hove: Psychology Press. Talarico, J. M., Berntsen, D. and Rubin, D. C. (2009). Positive emotions enhance recall of peripheral details. Cognition and Emotion, 23, 380–398. Talland, G. A. (1965). Deranged Memory. New York: Academic Press. Tandoh, K. and Naka, M. (2007). Durability of retrieval-induced forgetting. Shrinrigaku Kenku, 78, 310–315. Tanenhaus, M. K., Spivey-Knowlton, M. J., Eberhard, K. M. and Sedivy, J. C. (1995). Integration of visual and linguistic information in spoken language comprehension. Science, 268, 1632–1634.

448

References

Taylor, F. K. (1965). Cryptomnesia and plagiarism. British Journal of Psychiatry, 111, 1111–1118. Taylor, R. and O‘Carroll, R. (1995). Cognitive estimation in neurological disorders. British Journal of Clinical Psychology, 34, 223–228. Theeuwes, J. and Hagenzieker, M. P. (1993). Visual search of traffic scenes: On the effect of location expectations. In A. G. Gale (ed.) Vision in Vehicles IV (pp. 149–158). Amsterdam: Elsevier. Thomas, J. C. (1974). An analysis of behaviour in the hobbits-orcs problems. Cognitive Psychology, 6, 257–269. Thomas, N. J. T. (1999). Are theories of imagery theories of imagination? An active perception approach to conscious mental content. Cognitive Science, 23(2), 207–245. Thompson, L. A., Williams, K. L., L’Esperance, P. R. and Cornelius, J. (2001). Context-dependent memory under stressful conditions: The case of skydiving. Human Factors, 43, 611–619. Thompson, V. A. (2009). Dual process theories: A metagcognitive perspective. In J. St. B. T. and K. Frankish (eds) In Two Minds: Dual Processes and Beyond (pp. 171–198). Oxford: Oxford University Press. Thompson, V. A., Evans, J. St. B. T. and Handley, S. J. (2005). Persuading and dissuading by conditional argument. Journal of Memory and Language, 53, 238–257. Thorndike, E. L. (1898). Animal intelligence: An experimental study of the associative processes in animals. Psychological Monographs, 2, No. 8. Thorndike, E. L. (1914). The Psychology of Learning. New York: Teachers College. Tipper, S. P. (1985). The negative priming effect: Inhibitory effects of ignored primes. Quarterly Journal of Experimental Psychology, 37A, 571–590. Tipper, S. P. and Cranston, M. (1985). Selective attention and priming: The inhibitory and facilitatory effects of ignored primes. Quarterly Journal of Experimental Psychology, 37A, 591–611. Tippett, L. J., Miller, L. A. and Farah, M. J. (2000). Prosopamnesia: A selective impairment in face learning. Cognitive Neuropsychology, 17, 1–3. Tisserand, D. J. and Jolles, J. (2003). On the involvement of prefrontal networks in cognitive ageing. Cortex, 39, 1107–1128. Toffalo, M. B. J., Smeets, M. A. M. and van den Hout, M. A. (2012). Proust revisited: Odours as triggers of aversive memories. Cognition and Emotion, 26(1), 83–92. Tomson, S. N., Avidan, N., Lee, K. et al. (2011). The genetics of colored sequence synesthesia:

Suggestive evidence of linkage to 16q and genetic heterogeneity for the condition. Behavioural Brain Research, 223(1), 48–52. Treisman, A. (1960). Contextual cues in selective listening. Quarterly Journal of Experimental Psychology, 12, 242–248. Treisman, A. (1964). Verbal cues, language and meaning in selective attention. American Journal of Psychology, 77, 206–219. Treisman, A. (1986). Features and objects in visual processing. Scientific American, 255, 106–115. Treisman, A. (1988). Features and objects: The fourteenth Bartlett memorial lecture. Quarterly Journal of Experimental Psychology, 40A, 201–237. Treisman, A. (1993). The perception of features and objects. In A. Baddeley and L. Weiskrantz (eds) Attention: Selection, Awareness and Control. A Tribute to Donald Broadbent (pp. 5–35). Oxford: Clarendon Press. Treisman, A. M. (1999). Feature binding, attention and object perception. In G. W. Humphreys, J. Duncan and A. Treisman (eds) Attention Space and Action: Studies in Cognitive Neuroscience (pp. 91–111). Oxford: Oxford University Press. Treisman, A. M. and Gelade, G. (1980). A feature integration theory of attention. Cognitive Psychology, 12, 97–136. Troscianko, E. (2013). Cognitive realism and memory in Proust’s madaleine episode. Memory Studies, published online, doi: http://dx.doi. org/10.1177/1750698012468000. Trueswell, J. C. (1996). The role of lexical frequency in syntactic ambiguity resolution. Journal of Memory and Language, 35, 566–585. Tsuruhara, A., Nakato, E., Otsuka, Y., Kanazawa, S., Yamaguchi, M. K. and Hill, H. (2011). The hollow-face illusion in infancy: Do infants see a screen based rotating hollow mask as hollow? i-Perception, 2, 418–427. Tuckey, M. R. and Brewer, N. (2003). How schemas affect eyewitness memory over repeated retrieval attempts. Applied Cognitive Psychology, 17, 785–800. Tulving, E. (1972). Episodic and semantic memory. In E. Tulving and W. Donaldson (eds) Organisation and Memory. New York: Academic Press. Tulving, E. (1976). Ecphoric processes in recall and recognition. In J. Brown (ed.) Recall and Recognition. New York: Wiley. Tulving, E. (1979). Relation between encoding specificity and levels of processing. In L. S. Cermak and F. I. M. Craik (eds) Levels of

References Processing in Human Memory. Hillsdale, NJ: Lawrence Erlbaum Associates. Tulving, E. (1983). Elements of Episodic Memory. Oxford: Clarendon Press. Tulving, E. (1985). How many memory systems are there? American Psychologist, 40, 385–398. Tulving, E. (1989). Memory: Performance, knowledge, and experience. The European Journal of Cognitive Psychology, 1, 3–26. Tulving, E. (2001). The origin of autonoesis in episodic memory. In H. L. Roediger and J. S. Nairne (eds) The Nature of Remembering: Essays in Honour of Robert G. Crowder. Washington, DC: American Psychological Association. Tulving, E. (2002). Episodic memory: From mind to brain. Annual Review of Psychology, 53, 1–25. Tulving, E. and Thomson, D. M. (1971). Retrieval processes in recognition memory: Effects of associative context. Journal of Experimental Psychology, 87, 116–124. Tulving, E. and Thomson, D. M. (1973). Encoding specificity and retrieval processes in episodic memory. Psychological Review, 80, 352–373. Tulving, E., Schacter, D. L. and Stark, H. A. (1982). Priming effects in word fragment completion are independent of recognition memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 17, 595–617. Turner, M. L. and Engle, R. W. (1989). Is working memory capacity task-dependent? Journal of Memory and Language, 28, 127–154. Tweney, R. D., Doherty, M. E., Worner, W. J., Pliske et al. (1980). Strategies of rule discovery in an inference task. Quarterly Journal of Experimental Psychology, 32, 109–123. Ucros, C. G. (1989). Mood state-dependent memory: A meta-analysis. Cognition and Emotion, 3, 139–167. Underwood, B. J. and Postman, L. (1960). Extraexperimental sources of interference in forgetting. Psychological Review, 67, 73–95. Ungerleider, L. G. and Mishkin, M. (1982). Two cortical visual sysems. In D. J. Ingle, M. A. Goodale and R. J. W. Mansfield (eds) Analysis of Visual Behaviour. Cambridge, MA: MIT Press. Vallar, G. and Baddeley, A. D. (1982). Short-term forgetting and the articulatory loop. Quarterly Journal of Experimental Psychology, 34A, 53–60. Vallar, G. and Baddeley, A. D. (1984). Fractionation of working memory: Neuropsychological evidence for a phonological short-term store.

449

Journal of Verbal Learning and Verbal Behaviour, 23, 151–161. Vallar, G., Bottini, G., Rusconi, M. L. and Sterzi, R. (1993). Exploring somatosensory neglect by vestibular stimulation. Brain, 116, 71–86. Vallar, G., Di Betta, A. M. and Silveri, M. C. (1997). The phonological short-term store rehearsal system: Patterns of impairment and neural correlates. Neuropsychologia, 35, 795–812. Vallée-Tourangeau, F. and Payton, T. (2008). Graphical representation fosters discovery in the 2–4–6 task. The Quarterly Journal of Experimental Psychology, 61, 625–640. Van Leeuwen, T. M., den Ouden, H. E. and Hagoort, P. (2011). Effective connectivity determines the nature of subjective experience in graphemecolor synesthesia. The Journal of Neuroscience, 31(27), 9879–9884. Varley, R. and Siegal, M. (2000). Evidence for cognition without grammar from causal reasoning and “theory of mind” in an agrammatic aphasic patient. Current Biology, 15(10), 723–726. Varley, R. A., Klessinger, N. J., Romanowski, C. A. and Siegal, M. (2005). Agrammatic but numerate. Proceedings of the National Academy of Sciences of the USA, 102(9), 3519–3524. Epub 2005 Feb 15. Velten, E. (1968). A laboratory task for induction of mood states. Behaviour Research and Therapy, 6, 473–482. Verfaillie, M. and Roth, H. L. (1996). Knowledge of English vocabulary in amnesia: An examination of premorbidly acquired semantic memory. Journal of the International Neuropsychology Society, 5, 443–453. Verfaillie, M., Koseff, P. and Alexander, M. P. (2000). Acquisition of novel semantic information in amnesia: Effects of lesion location. Neuropsychologia, 38, 484–492. Verhaeghen, P. (2011). Ageing and executive control: Reports of a demise greatly exaggerated. Current Directions in Psychological Science, 20, 174–180. Verschueren, N., Schaeken, W. and d’Ydewalle, G. (2005). A dual-process specification of causal conditional reasoning. Thinking and Reasoning, 11, 239–278. Victor, M., Adams, R. D. and Collings, G. H. (1989). The Wernicke-Korsakoff Syndrome and Related Neurologic Disorders due to Alcoholism and Malnutrition (2nd edn). Philadelphia: Davis. Vitevitch, M. S. and Luce, P. A. (1998). When words compete: Levels of processing in perception of spoken words. Psychological Science, 9, 325–329.

450

References

Vitevitch, M. S. and Luce, P. A. (1999). Probabilistic phonotactics and neighborhood activation in spoken word recognition. Journal of Memory and Language, 40, 374–408. Vitevitch, M. S. and Luce, P. A. (2005). Increases in phonotactic probability facilitate spoken nonword repetition. Journal of Memory and Language, 52, 193–204. Vlahovic, T. A., Roberts, S. and Dunbar, R. (2012). Effects of duration and laughter on subjective happiness within different modes of communication. Journal of Computer-Mediated Communication, 17(4), 436–450. Voeller, K. K. S. and Heilman, K. M. (1988). Attention deficit disorder in children: A neglect syndrome? Neurology, 38, 806–808. Vroomen, J. and de Gelder, B. D. (1997). Activation of embedded words in spoken word recognition. Journal of Experimental Psychology: Human Perception and Performance, 23, 710–720. Vroomen, J. and de Gelder, B. D. (2000). Sound enhances visual perception: Cross-modal effects of auditory organization on vision. Journal of Experimental Psychology: Human Perception and Performance, 26(5), 1583–1590. Vroomen, J., Bertelson, P. and de Gelder, B. D. (2001). The Ventriloquist Effect does not depend on the direction of automatic visual attention. Perception and Psychophysics, 63(4), 651–659. Wada, Y. and Yakamoto, T. (2001). Selective impairment of facial recognition due to a maematoma restricted to the right fusiform and lateral occipital region. Journal of Neurology, Neurosurgery and Psychiatry, 71, 254–257. doi:10.1136/jnnp.71.2.254. Wagenaar, W. A. (1986). My memory: A study of autobiographical memory over six years. Cognitive Psychology, 18, 225–252. Wagenaar, W. A. (1994). The subjective probability of guilt. In G. Wright and P. Ayton (eds) Subjective Probability. Chichester: John Wiley. Wager, T. and Smith, E. E. (2003). Neuroimaging studies of working memory: A meta-analysis. Cognitive, Affective, and Behavioural Neuroscience, 3, 255–274. Wagner, G. P., MacPherson, S. E., Parente, M. A. M. P. and Trentini, C. M. (2011). Cognitive estimation abilities in healthy and clinical populations: The use of the Cognitive Estimation Test. Neurological Sciences, 32, 203–210. Walker, B. N. and Kramer, G. (2004). Ecological psychoacoustics and auditory displays: Hearing,

grouping and meaning making. In J. G. Neuhoff (ed.) Ecoloical Psychoacoustics. London: Academic Press. Ward, J. (2010). The Student’s Guide to Cognitive Neuroscience (2nd edn). Hove: Psychology Press. Ward, J. (2013). Synesthesia. Annual Review of Psychology, 64, 49–75. Ward, J., Li, R., Salih, S. and Sagiv, N. (2007). Varieties of grapheme-colour synaesthesia: A new theory of phenomenological and behavioural differences. Consciousness and Cognition, 16(4), 913–931. Warren, E. W. and Groome, D. H. (1984). Memory test performance under three different waveforms of ECT for depression. British Journal of Psychiatry, 144, 370–375. Warren, J. E., Wise, R. J. and Warren, J. D. (2005). Sounds do-able: Auditory-motor transformations and the posterior temporal plane. Trends in Neurosciences, 28(12), 636–643. Epub 2005 Oct 10. Warrington, E. K. (1986). Memory for facts and memory for events. British Journal of Clinical Psychology, 25, 1–12. Warrington, E. K. and Weiskrantz, L. (1968). A new method of testing long-term retention with special reference to amnesic patients. Nature, 217, 972–974. Warrington, E. K. and Shallice, T. (1969). The selective impairment of auditory-verbal short-term memory. Brain, 92, 885–896. Warrington, E. K. and Weiskrantz, L. (1970). Amnesic syndrome: Consolidation or retrieval? Nature, 228, 628–630. Warrington, E. K. and Shallice, T. (1972). Neuropsychological evidence of visual storage in short-term memory tasks. Quarterly Journal of Experimental Psychology, 24, 30–40. Warrington, E. K. and Shallice, T. (1979). Semantic access dyslexia. Brain, 102, 43–63. Warrington, E. K. and Shallice, T. (1984). Category specific semantic impairments. Brain, 107, 829–853. Wason, P. C. (1960). On the failure to eliminate hypotheses in a conceptual task. Quarterly Journal of Experimental Psychology, 12, 129–140. Wason, P. C. (1968). Reasoning about a rule. Quarterly Journal of Experimental Psychology, 23, 63–71. Wason, P. C. and Shapiro, D. (1971). Natural and contrived experience in a reasoning problem. Quarterly Journal of Experimental Psychology, 23, 63–71.

References Waters, E. A. (2008). Feeling good, feeling bad, and feeling at risk: A review of incidental affect’s influence on likelihood estimates of health hazards and life events. Journal of Risk Research, 11, 569–595. Watson, J. B. (1913). Psychology as the behaviourist views it. Psychological Review, 20, 158–177. Wearing, D. (2005). Forever Today. London: Transworld. Weeks, D., Freeman, C. P. L. and Kendell, R. E. (1980). ECT: II. Enduring cognitive deficits? British Journal of Psychiatry, 137, 26–37. Wegner, D. M. (2003). The mind’s best trick: How we experience conscious will. Trends in Cognitive Sciences, 7, 65–69. Weinberg, J., Diller, L., Gordon, W., Gertsman, L. et al. (1977). Visual scanning training effect on reading -related tasks in acquired right brain damage. Archives of Physical Medicine and Rehabilitation, 58, 479–486. Weisberg, R. W. and Alba, J. W. (1981). An examination of the alleged role of “fixation” in the solution of several “insight” problems. Journal of Experimental Psychology: General, 110, 169–192. Weiskrantz, L. (1986). Blindsight: A Case Study and Implications. Oxford: Clarendon Press. Weiskrantz, L., Warrington, E. K., Sanders, M. D. and Marshall, J. (1974). Visual capacity in the hemianopic field following a restricted occipital ablation. Brain, 97, 709–728. Weiss, P. H. and Fink, G. R. (2009). Graphemecolour synaesthetes show increased grey matter volumes of parietal and fusiform cortex. Brain, 132, 65–70. Weiss, P. H., Zilles, K. and Fink, G. R. (2005). When visual perception causes feeling: Enhanced cross-modal processing in grapheme-color synesthesia. NeuroImage, 28, 859–68. Welford, A. T. (1952). The psychological refractory period and the timing of high speed performance: A review and a theory. British Journal of Psychology, 43, 2–19. Welt, L. (1888). Über Charakterveranderungen des Menschen infolge von Läsionen des Stirnhirns Deutsche Archiv für Klinische Medizin, 42, 339–390. Wernicke, C. (1874). Der Aphasiche Symptomkomplex: Eine Psychologische Studie Aufanatomischer Basis. Breslau: Cohn and Weigert. Wernicke, C. (1881). Lehrbuch der gehirnkrankheiten fur aerzte und studirende, Vol. 2 (pp. 229–242). Kassel Theodor Fischer. Wertheimer, M. (1912). Experimentelle studien uber das sehen von bewegung. Zeitschrift fur Psychologie, 61, 161–265.

451

Wertheimer, M. (1923). Untersuchungen zur Lehre von der Gestalt. Zeitschrift Forschung, 4, 301–350. Wessinger, C. M., Fendrich, R. and Gazzaniga, M. S. (1997). Islands of residual vision in hemianopic patients. Journal of Cognitive Neuroscience, 9, 203–221. West, M. J., Coleman, P. D., Flood, D. G. and Troncoso, J. C. (1994). Differences in the pattern of hippocampal neuronal loss in normal ageing and Alzheimer’s disease. The Lancet, 344, 769–772. Westwood, D. A. and Goodale, M. A. (2003). Perceptual illusion and the realtime control of action. Spatial Vision, 16, 243–254. Westwood, D. A. and Goodale, M. A. (2011). Converging evidence for diverging pathways: Neuropsychology and psychophysics tell the same story. Vision Research, 51(8), 804–811. Wetherick, N. E. (1962). Eliminative and enumerative behaviour in a conceptual task. Quarterly Journal of Experimental Psychology, 14, 129–140. Whitlow, S. D., Althoff, R. R. and Cohen, N. J. (1995). Deficit in relational (declarative) memory in amnesia. Society for Neuroscience Abstracts, 21, 754. Whitty, C. W. M. and Zangwill, O. L. (1976). Amnesia. London: Butterworths. Wickelgren, W. A. (1968). Sparing of short-term memory in an amnesic patient: Implications for strength theory of memory. Neuropsychologia, 6, 235–244. Wilkins, A. J., Shallice, T. and McCarthy, R. (1987). Frontal lesions and sustained attention. Neuropsychologia, 25, 259–365. Williams, S. J., Wright, D. B. and Freeman, N. H. (2002). Inhibiting children’s memory of an interactive event: The effectiveness of a cover-up. Applied Cognitive Psychology, 16, 651–664. Wilson, B. A. (1987). Rehabilitation of Memory. New York: Guilford. Wilson, B. A. (2004). Management and rehabilitation of memory problems in brain-injured adults. In A. D. Baddeley, M. D. Kopelman and B. A. Wilson (eds) The Essential Handbook of Memory Disorders for Clinicians. Chichester: Wiley. Wilson, B. A. and Wearing, D. (1995). Amnesia in a musician. In R. Campbell and M. Conway (eds) Broken Memories. Oxford: Blackwell. Wilson, B. A., Kazniak, A. W. and Fox, J. H. (1981). Remote memory in senile dementia. Cortex, 17, 41–48. Wilson, B. A., Baddeley, A. D. and Kapur, N. (1995). Dense amnesia in a professional musician following herpes simplex virus encephalitis. Journal

452

References

of Clinical and Experimental Neuropsychology, 17, 668–681. Wilson, B. A., Gracey, F., Evans, J. J. and Bateman, A. (2009). Neuropsychological Rehabilitation: Theory, Models, Therapy and Outcome. Cambridge: Cambridge University Press. Wilson, C. E., Palermo, R., Schmalzl, L. and Brock, J. (2010). Specificity of impaired facial identity recognition in children with suspected developmental prosopagnosia. Cognitive Neuropsychology, 27(1), 30–45. Wilson, D. and Sperber, D. (2002). Truthfulness and relevance. Mind, 111, 583–632. Wilson, M. and Wilson, T. P. (2005). An oscillator model of the timing of turn-taking. Psychonomic Bulletin and Review, 12(6), 957–968. Wingate, M. E. (1976). Stuttering: Theory and Treatment. New York: Irvington. Winograd, E. (1976). Recognition memory for faces following nine different judgements. Bulletin of the Psychonomic Society, 8, 419–421. Wise, R. J., Greene, J., Büchel, C. and Scott, S. K. (1999). Brain regions involved in articulation. Lancet, 27, 353(9158), 1057–1061. Witthoft, N. and Winawer, J. (2013). Learning, memory, and synesthesia. Psychological Science, 24, 258–65. doi: 10.1177/0956797612452573. Wolters, G. and Goudsmit, J. J. (2005). Flashbulb and event memory of September 11, 2001: Consistency, confidence and age effects. Psychological Reports, 96, 605–619. Wolters, G. and Raffone, A. (2008). Coherence and recurrency: Maintenance, control, and integration in working memory. Cognitive Processing, 9, 1–17. Wood, N. and Cowan, N. (1995). The cocktail party phenomenon revisited: How frequent are attention shifts to one’s name in an irrelevant auditory channel? Journal of Experimental Psychology, Learning Memory and Cognition, 2, 255–260. Wright, D. B., Self, G. and Justice, C. (2000). Memory conformity: Exploring misinformation effects when presented by another person. British Journal of Psychology, 91, 189–202. Wright, D. B., Loftus, E. F. and Hall, M. (2001). Now you see it, now you don’t: Inhibiting recall in the recognition of scenes. Applied Cognitive Psychology, 15, 471–482. Yaro, C. and Ward, J. (2007). Searching for Shereshevskii: what is superior about the memory of synaesthetes? Quarterly Journal of Experimental Psychology, 60(5), 681–695.

Young, A. W. and Burton, A. M. (1999). Simulating face recognition: Implications for modelling cognition. Cognitive Neuropsychology, 16, 1–48. Young, M. J., Tiedens, L. Z., Jung, H. and Tsai, M.-H. (2011). Mad enough to see the other side: Anger and the search for disconfirming information. Cognition and Emotion, 25, 10–21. Zacher, W. (1901). Über ein Fall von doppelseitigem, symmetrisch gelegenem Erweichungsherd im Stirnhirn und Neuritis optica. Neurologisches Zentralblatt, 20, 1074–1083. Zanetti, O., Zanieri, G., Giovanni, G. D., de Vreese, L. P. et al. (2001). Effectiveness of procedural memory stimulation in mild Alzheimer’s disease patients. In L. Clare and R. T. Woods (eds) Cognitive Rehabilitation in Dementia: A Special Issue of Neuropsychological Rehabilitation. Hove: Psychology Press. Zaragoza, M. S. and Lane, S. M. (1998). Processing resources and eyewitness suggestibility. Legal and Criminological Psychology, 3, 294–300. Zeki, S. (2003). The disunity of consciousness. Trends in Cognitive Sciences, 7, 214–218. Zevin, J. D. and Seidenberg, M. S. (2002). Age of acquisition effects in reading and other tasks. Journal of Memory and Language, 47, 1–29. Zevin, J. D. and Seidenberg, M. S. (2004). Age of acquisition effects in reading aloud: Tests of cumulative frequency and frequency trajectory. Memory and Cognition, 32, 31–38. Zhu, B., Chen, C., Loftus, E. F., Lin, C., He, Q., Chen, C. et al. (2010). Individual differences in false memory from misinformation: Cognitive factors. Memory, 18, 543–555. Zihl, J. (1994). Rehabilitation of visual impairments in patients with brain damage. In A. C. Koijman, P. L. Looijjjeesijn, J. A. Welling and G. J. van der Wildt (eds) Low Vision (pp. 287–295). Amsterdam: IOS Press. Zihl, J. (1995). Eye movement patterns in hemianopic dyslexia. Brain, 118, 891–912. Zola-Morgan, S. and Squire, L. R. (2000). The medial temporal lobe and the hippocampus. In E. Tulving and F. I. M. Craik (eds) The Oxford Handbook of Memory. Oxford: Oxford University Press. Zwisterlood, P. (1989). The locus of the effects of sentential-semantic context in spoken-word processing. Cognition, 32(1), 25–64.

Author index Abelson, R.P. 164 Ackerly, S. 276 Addis, D.R. 179, 224 Aggleton, J.P. 14, 163, 216 Aglioti, S. 63 Alba, J.W. 244 Albert, M.S. 212–213 Alderman, N. 292 Alexander, M.P. 149, 297 Allen, G.A. 185, 194 Altmann, E.M. 160 Altmann, G.M.T. 323–325 Alzheimer, A. 206 Ames, A. 33–34 Amir, N. 184, 189 Amodio, D.M. 184 Anderson, B. 116 Anderson, J.M. 348 Anderson, J.R. 95, 171, 257 Anderson, M.C. 155, 160, 187–189, 203 Andreewsky, E. 344 Andrewes, D. 233, 278, 293 Andrews, B. 199 Andrews, P.W. 385, 390 Andrews, S. 315, 317 Anolli, L. 252–253 Asher, J.E. 104 Ask, K. 387 Aslan, A. 191 Assal, G. 131 Atkinson, R.C. 137–138 Auerbach, S.H. 350 Avesani, R. 125 Avidan, G. 133–134 Azzopardi, P. 110, 112 Baddeley, A.D. 19, 89, 138–139, 142–151, 154–155, 175, 183, 203, 209–210, 226, 237, 239, 273, 294, 395 Bahrick, H.P. 159, 193 Bailey, C.H. 17 Bailey, P.J. 306 Baizer, J.S. 47 Baker, J. 396 Balani, A.B. 280 Baldo, J.V. 286 Ball, L.J. 261, 264 Balota, D.A. 314–317 Bamdad, M.J. 297 Banaji, M.R. 184

Banich, M.T. 50, 69 Barceló, F. 284 Barnett, K.J. 104 Barnier, A.J. 191 Baron, J.315 Baron-Cohen, S. 20, 100–104, 108 Bartlett, F.C. 7–8, 160–162, 165, 198 Barton, J.J.S. 126, 129, 133–134 Basden, B.H. 190 Basden, D.R. 190 Basso, A. 139 Bate, S. 134 Bauer, R.M. 132 Bauml, K-H. 190 Bayley, P.J. 226 Bearman, C. 254, 256–257 Beck, A.T. 177 Beck, D.M. 49–50 Becker, J.T. 210 Becklen, P. 84 Behrman, M. 133–134 Beilock, S.L. 96 Bellas, D.N. 113 Bellugi, U. 148 Bench, C.J. 280 Benson, D.F. 348 Bentall, R. 232–233 Bentin, S. 133 Benton, A.L. 278 Benton, T.R. 200 Beranek, L.L. 55 Berko-Gleason, J. 334 Berntsen, D. 194 Berrios, G.E. 197 Bertera, J.H. 359–360 Berti, A. 116 Besner, D. 144 Bialystock, E. 73 Bianchi, L. 276 Biederman, I. 30 Bishop, D.V.M. 365–366 Bisiach, E. 114, 116 Bjork, E.L. 160, 186, 190 Bjork, R.A. 160, 186 Blackmore, S. 21, 23 Blaiss, C.A. 192 Blakemore, C. 102 Blakemore, S.J. 358 Blanchette, I. 254, 256, 383, 388, 395, 397

Blank, S.C. 357 Blesser, B. 353 Bliss, T.V.P. 17 Blix, I. 189 Bluck, S. 195 Bock, J.K. 328 Bodamer, J. 126 Bogen, G.M. 347 Bogen, J.E. 347 Boies, S.J. 90 Bornstein, B. 131 Bottini, G. 107 Boucher, V.J. 326 Bourne, V. 135 Boutsen, L. 128 Bowen, A. 114 Bower, G.H. 171, 177 Braine, M.D.S. 264–265 Brainerd, C.J. 270 Brandt, K.R. 223 Bransford, J.D. 162–163 Brennen, T. 189 Brewer, N. 164, 197 Brewin, C.R. 189 Brickner, R.M. 276 Bridgeman, B. 47–48 Bright, D.A. 386 Broadbent, D.E. 12, 75 Broca, P. 14, 274, 337–339, 341, 343, 346–349, 351–352, 357–358 Brockmole, J.R. 152 Broeders, R. 394 Broman, M. 237 Brown, A.S. 184, 215 Brown, C. 201–202 Brown, J. 140 Brown, R. 196, 377 Bruce, V. 46, 126–127, 129, 132, 135 Bruner, J.S. 259 Bruyer, R. 130–131 Buckner, R.L. 179 Budson, A.E. 197 Bull, R. 201 Bullier, J. 47 Burgess, M.C.R. 167 Burgess, P.W. 19, 280, 285–286, 289–291, 293, 296–298 Burton, A.M. 132 Butterworth, B. 342 Byrne, R.M.J. 262, 265

454

Author index

Cabeza, R. 380 Cahill, L. 380 Cahir, C. 388 Calvo, M.G. 395 Camp, G. 187 Campbell, D. 276 Campbell, R. 133, 239 Campion, J. 110 Cantril, H. 164 Caplan, D. 356 Carpenter, S.K. 100, 102, 185–186, 194 Carroll, D.W. 334 Carroll, M. 189 Cavaco, S. 219 Cavenett, T. 373 Cermak, L.S. 218 Chalmers, D.J. 21 Chang, W. 67 Channon, S. 396 Chase, W.G. 163, 255 Chater, N. 268, 270 Chen, Z. 254 Cheng, P.W. 265–266 Cherry, E.C. 74 Cherry, K.E. 169 Chi, M.T.H. 255, 257 Chomsky, N. 366 Chronicle, E.P. 248 Chu, S. 176 Chun, M.M. 92 Cicerone, K. 281 Clancy, S.A. 378 Claparede, E. 220 Clare, L. 223, 237 Claret, P.L. 37 Clark, H.H. 334 Clark, L.A. 384 Claxton, G. 184 Cleary, A.M. 179 Cohen, G. 241 Cohen, L. 354–355 Cohen, N.J. 213, 219, 229 Colchester, A. 216 Cole, B.L. 38 Coleman, M.D. 386 Collette, F. 89,153, 299 Coltheart, M.T. 315, 320, 366 Compton, R.J. 50, 69 Conroy, M.A. 183, 221 Conway, M.A. 238–239 Conway, R.A. 87 Corbett, F. 224 Corbetta, M. 72, 74, 79 Corkin, S. 213–214, 216, 219 Corsi, P.M. 147 Corteen, R.S. 76 Cosky, M. 315 Cowan, N. 140–142. 151

Cowey, A. 67, 110–112 Cox, J.R. 263 Craik, F.I.M. 73, 141, 166–170, 173–174, 234 Cranston, M. 77 Creem, S.H. 47 Crew, C.M. 329 Crick, F. 19, 20 Crinella, F.M. 296 Crump, M.J.C. 96 Cunitz, A.R. 139–140 Cutler, A. 316 Dallas, M. 181 Damasio, A.R. 127, 277 Dando, C.J. 202 Davidson, J.E. 271 Davidson, P.S.R. 196–197 Davies, S.P. 249 Davis, D. 199, 378 Davis, M.H. 312 Dawes, R.M. 271 Day, R.H. 33 De Fockert, J.W. 86 De Gelder, B.D. 135, 312 De Graaf, T.A. 21 De Haan, E.H.F. 67, 132–133, 135 De Martino, B. 383–384 De Monte, V.E. 232 De Neys, W. 395 De Renzi, E. 114, 129–130 De Ruiter, J.P. 330 De Vries, M. 385, 388–389 De Zeeuw, C.I. 17 DeGelder, B. 54 DeGroot, A.D. 255 Dehaene , S. 21 DeHart, T. 375 Delaney, P. 191 Delis, D.C. 283 Dell, G.S. 327–329 Della Sala, S. 277 Deloche, G. 361 Denes, G. 279 Derakshan, N. 396 Desimone, R. 71, 114, 118 Deubel, H. 72 Deutsch, D. 56, 76 Deutsch, J.A. 76 Devlin, J.T. 359, 364 Di Lollo, V. 43–44 Ditto, P.H. 382 Dixon, M.J. 102–103,105 Dobler, V.B. 117 Dodds, C.M. 117 Dodson, C.S. 199 Downes, J.J. 176 Drace, S. 387

Drews, F.A. 92 Driver, J. 80–81, 97, 107, 115, 118 Dronkers, N.F. 351, 357 Drosopoulos, S. 180 Duchaine, B.C. 131, 133 Duffy, P.L. 103 Dumay, N. 313 Dunbar, K. 254, 256 Dunbar, R.I.M. 330, 333 Duncan, J. 71, 114, 118, 292, 295–296 Duncker, K. 243–244, 253 Dunn, D. 84–85 Dupoux, E. 305 Durie, B. 59–60 Easterbrook, J.A. 372–373 Ebbinghaus, H. 6, 63–64, 139, 158–160, 186 Edelstein, R.S. 373 Edgar, G.K. 40 Edworthy, J. 57–58 Egeth, H.E. 54 Eich, E. 376 Eichenbaum, H.E. 180, 229 Eisner, F. 314 Ellis, A.W. 315, 361–362 Elquayam S. 271 Endler, J.A. 35 Engle, R.W. 151–152 Enns, J.T. 43–44 Equist, J. 105 Eriksen, B.A. 85 Eriksen, C.W. 85 Esgate, A. 23, 155, 165, 203 Eskes, G.A. 221 Eslinger, P.J. 277 Evans, J. St. B.T. 258, 262–264, 269–271 Evans, M.E. 286–287 Evans, S. 354 Eysenck , M.W. 23, 155, 170, 190, 203, 373, 377, 381–382, 395–397 Farah, M.J. 119–120,124–125, 130, 148, 295 Feinberg, T. 342 Felleman, D.J. 44 Fellows, L.K. 300 Ferrier, D. 276 Fetkewicz, J. 378 Fiedler, K. 376 Fillmore, C.J. 308 Fimm, B. 117 Fink, G.R. 107 Finn, B. 192 Fisher, R.P. 173–174, 185, 201–202

Author index Fitch, G.M. 67 Fitts, P.M. 95 Fleischman, D.A. 234 Flin, R. 199 Fodor, J.A. 303. 333 Fornazzari, L. 100 Forster, S. 87 Fox, E. 397 Franz, V.H. 124 Frassinetti, F. 118 Frazier, L. 324 Frederick, S. 269 Freud, S. 342, 377–379, 396 Freund, C.S. 345 Fridja, N.384 Friederici, A.D. 354 Friedman, N.P. 149, 152, 298 Friesen, C.K. 80 Fromkin, V.A. 326–327 Fukuda, K. 152 Funell, E. 125 Gabbert, F. 202 Gable, P. 373–374 Gabrieli, J.D.E. 224 Gaffan, D. 230 Gainotti, G. 129 Gaissert, M. 61 Gale, M. 261 Galetta, K.M. 232 Galfano, G. 80 Gallace, A. 62–63 Galton, F. 101 Gardiner, J.M. 171, 181, 222, 224 Gardner, M.B. 52 Gardner, R.S. 52 Garrett, M. 327, 333 Garrett, W.E. 232 Garrido, L. 131, 350 Garrod, S. 331 Gathercole, S.E. 146 Gazzaniga, M.S. 14 Geiselman, R.E. 190, 200–202 Gelade, G. 55, 82–83 Gentner, D. 252, 256 Gentner, D.R. 252 George, M. 117 Geraerts, E. 199, 378–379 Gernsbacher, M.A. 315 Geschwind, N. 349 Gibson, J.J. 9, 45–46, 48, 56, 61 Gick, M.L. 253 Gilhooly, K.J. 242, 246–247 Glanzer, M. 139–140 Glenberg, A.M. 169 Glisky, E.L. 196–197, 219, 237 Gloning, I. 349 Gluck, J. 195

Godden, D.R. 175 Goel, V. 288–289 Gold, C.A. 197 Gold, J.M. 152 Goldberg, E. 300 Goldman-Rakic, P.S. 295 Goldstein, E.B. 50, 69 Goltz, F. 276 Gonnerman, L.M. 316 Goodale, M.A. 46–48, 63–65, 67, 113, 120, 123–124, 132, 135 Goodglass, H. 341, 344 Goodman-Delahunty, J. 386 Goodwin, D.W. 177 Gopie, N. 183 Gorelick, E.D. 351 Gorman, Margaret E. 260 Gorman, Michael E. 260 Goswami, U. 314, 367 Gotlib, I.H. 396 Goudsmit, J.J. 197 Gough, P. 315 Graf, P. 182–183, 220–221 Grafman, J. 279, 289, 297 Graham, K.S. 224, 230 Granhag, P.A. 387 Grant, N. 188 Gray, R. 66 Greene, J.D. 391–393 Greenough, W.T. 17 Greenspoon, J. 174 Greenwald, A.G. 184, 91 Gregory, R.L. 31–32, 41–42, 44, 48 Grice, H.P. 331–332 Griffin, Z.M. 329 Griffiths, T.D. 350 Griggs, R.A. 263 Grimm, J.L.C. 25 Grimm, W.C. 25 Grisham, J.R. 383 Griskevicius, V. 372, 388–390 Groome, D.H. 23, 155, 165, 187–188, 190, 203, 232 Grossenbacher, P.G. 102 Habib, R. 17 Hackett, T.A. 53 Hagenzieker, M.P. 38 Haier, R.J. 14 Hall, D.A. 354 Halligan, P.W. 114–116 Halstead, W.C. 281 Handy, T.C. 46 Happé, F. 368 Harding, A. 216 Hareli, S. 385 Harenski, C.L. 394

455

Harley, T. 310, 326–327, 334, 369 Harlow, J.M. 275 Harmon-Jones, E. 373–374 Harrison, J. 135 Harsch, N. 196–197 Hart, J. 17 Hartley, T. 230 Hastie, R. 271 Hastorf, A.H. 164 Hauser, M. 392 Hawkins, K. 117 Hawkins, S. 333 Haxby, J. 129 Hayashi T. 34 Hayes, J.R. 249 Hayman, C.A.G. 182 Hayne, H. 195 Haynes, J.D. 11, 28 Head, H. 339, 369 Heathcote, D. 155 Hebb, D.O. 15–17, 31 Heilman, K.M. 117, 342–346, 349 Heller, M.A. 62 Helmstaedter, C. 284 Henriques, D.Y. 61 Henson, R.N.A. 153 Hermann, L. 32 Herrmann, D. 165 Hersh, N. 238 Heywood, C.A. 135 Hickok, G. 53, 355 Hill, C. 259 Hill, E. 149 Hills, B.L. 38 Hinton, G.E. 363 Hiraoka, K. 125 Hitch, G.J. 138, 142–143, 154 Ho, C.E. 81, 47 Hodges, J.R. 224 Hofman, P.A.M. 232 Holcomb, P.J. 320 Hole, G. 135 Holland, A.C. 375 Holyoak, K.J. 253, 265 Horowitz, M.J. 189 Howell, P. 367 Hu, Y. 64–65 Hubbard, E.M. 106–107 Hubel, D.H. 11, 28 Hughes, P.K. 38 Hulme, C. 141, 144, 152, 369 Humphreys, G.W. 84–85, 114, 120–122, 125, 128 Hunt, R.R. 169–170 Hupbach, A. 192 Hupe, J. M. 44, 106 Huppert, F.A. 180, 221–222 Husain, M. 50

456

Author index

Husserl, E. 48 Hyde, T.S. 167 Hyden, H. 15 Jacobsen, C.F. 277 Jacoby, L.L. 181 Jacquemot, C. 303, 354 James, W. 6, 71, 137–138 Janak, P.H. 192 Jansma, J.M. 94 Janssen, W. 66 Janssen, S.M.J. 195 Jared, D. 316 Jastrowitz, M. 276 Java, R.I. 181 Jenkins, J.J. 167 Jerabek, I. 175 Jewanski, J. 100 Joanisse, M.F. 323 Johnson, A. 385 Johnson, J.A. 90 Johnson, M.K. 162–163 Johnson-Laird, P. 19, 263, 266–267, 390, 391, 395 Johnstone, E.C. 232 Johnstone, L. 233 Jolles, J. 234 Jones, D.M. 145 Jonides, J. 153 Joormann, J. 396 Joseph, R. 116 Juhasz, B.J. 315 Jung, R.E. 14 Jurado, M.B. 300 Kaas, J.H. 53 Kahneman, D. 85–86, 269 Kandel, E.R. 17 Kane, M.J. 152 Kant, I. 37 Kanwisher, N. 129 Kaplan, E. 341 Kapur, N. 213, 215, 238 Karat, J. 247 Karnath, H.O. 116, 118, 135 Katz, R.B. 344 Keane, M.T. 23, 397, 253–254 Kelley, L.A. 35 Kelly, J. 312 Keltner, D. 386 Kenealy, P.M. 376–377 Kensinger, E.A. 375, 380 Kentridge, R. 111 Keren, G. 391 Kerns, J.G. 396 Kertesz, A. 349 Kihlstrom, J.F. 177, 235, 375 Kimball, J. 324 Kimberg, D.Y. 295

King, J.A. 180, 222–223 King, N.S. 231 Kingstone, A. 80 Kinsbourne, M. 118 Kintsch, W. 171 Kirdendall, D.T. 232 Kirwilliam, S. 231 Klatzky, R.L. 61, 63 Klauer, K.C. 148 Klein, D.E. 172 Knight, R.T. 284 Knoblich, G. 249–250 Koch, C. 19 Koehnken, G. 201 Koenigs, M. 394 Koffka, K. 7 Köhler, W. 7, 242–243 Kolb, B. 274 Kopelman, M.D. 209, 212–213, 216, 220–223, 227–228, 234 Koriat, A. 164 Korsakoff, S.S. 206, 210, 230 Kousta, S.T. 318 Kozak, K. 66 Kramer, G. 55 Kraut, M.A. 17 Krueger, L.E. 199 Kuffler, S.W. 28 Kuhbandner, C. 190 Kuhl, B.A. 14 Kulik, J. 196, 377 Külpe, O. 242 Kurtz, K.J. 256 Kussmaul, A. 342–345, 358, 369 LaBar, K.S. 72, 380 Laberge, D. 85 Laird, J. 295 Landis, T. 231 Lane, S.M. 198 Lang, A.J. 189 Langham, M. 39 Lashley, K. 15 Lavie, N. 78, 85–87, 90 Law, R.190 Lawson, J.R. 117 Leach, C.W. 385 Lederman, S.J. 61, 63 Lee, A.C.H. 223, 226, 230 Legrenzi, P. 268 Lench, H.C. 382 Lerner, J.S. 382, 385–387, 397 Levelt, W.J.M. 309, 326, 328–329, 337, 339 Levine, B. 212, 301 Levine, L.J. 373, 382 Levy, J. 91–92 Lewis, V.J. 144, 146

Lhermitte, F. 279 Libet, B. 21 Lichtheim, L. 339–345, 348, 358, 369 Liebenthal, E. 354 Lief, H. 378 Lien, M.C. 91 Lindsay, D.S. 199 Linton, M. 194 Lisker, L. 312 Lissauer, I.R. 119–120 Litvak, P.M. 386–387, 397 Liu, X. 96 Local, J. 312 Lockhart, R.S. 166, 168–169 Loeb, J. 276 Loewenstein, J. 256 Loftus, E.F. 198–199, 373–374, 378 Logan, G. D. 96 Logie, R.H. 148,151, 152 Logothesis, N.K. 47 Lomo, T. 17 Lorayne, H. 165 Lorian, C.N. 383 Loveday, C. 238 Lovelace, C.T. 102, 107 Lucas, J. 165 Luce, P.A. 313 Luchins, A.S. 244 Luria, A.R. 13, 273 Luzzatti, C. 114, 116 Lynch, J.S. 264 MacGregor, J.N. 248 Macken, W.J. 145 MacLeod, C.M. 18 MacLeod, M.D. 187–189, 200 Macmillan, M.B. 275 Macrae, C.N. 187, 189 MacSweeney, M. 307 Maier, N.R.F. 243, 254 Mair, W.G.P. 213 Majerus, S. 146 Malhotra, P.A. 117 Mandler, G. 18, 20, 170–171, 179–180, 221, 229 Maner, J.K. 383 Manktelow, K.L. 271 Manly, T. 116–117 Mannoni, L. 69 Mantyla, T. 171 Marcel, A.J. 76–77 Marr, D. 11, 29, 30, 38 Marshall, J.C. 114–116, 362 Marslen-Wilson, W. 319 Martin, E.A. 396 Martin, R.C. 146 Mattingley, J.B. 102, 104

Author index Mattson, A.J. 129 Mattys, S.L. 313 Maurer, D. 107 Mayes, A.R. 215 McCall, W.V. 233 McCarthy, G. 129 McCarthy, R.A. 225, 227 McClelland, J. L. 11, 30, 320, 322–323 McDaniel, M.A. 169, 185–186 McDonald, P.V. 60 McDowd, J.M. 234 McGeoch, J.A. 159 McGettigan, C. 355–356 McGinn, C. 21 McGurk, H. 54 McIntosh, R.D. 114 McLelland, J.L. 125 McLeod, P.D. 90 McNally, R.J. 378–379 McNeil, J.E. 131 McQueen, J.M. 313–314 McRae, K. 316 Meeter, M. 159, 232 Melby-Lervag, M. 152 Memon, A. 198, 201 Mendez, M.F. 348 Meredith, C. 57 Mesulam, M. 118, 351 Metzler, J. 26–27, 30 Michel, F. 344 Middlebrooks, C.J. 52 Milders, M.V. 237 Miller, G.A. 14, 141, 165 Miller, E. 210 Miller, L.A. 283 Mills, C.B. 104 Milne, R. 201 Milner, A.D. 46–48, 63, 113, 120, 123–124, 132, 135 Milner, B. 14, 208, 214, 216, 220, 226–227, 282, 287 Miozzo, M. 329 Miranda, R. 177, 375 Misanin, J.R. 191 Mishkin, M. 46, 48, 72 Mitchell, D.B. 182 Miyake, A. 89, 149, 152, 298 Mohr, J.P. 347 Mondloch, C.J. 107 Monnot, M. 351 Moray, N. 87 Moretto, G. 394 Morris, P.E. 163 Morris, R.D. 210 Morris, R.G. 288 Morrison, C.M. 315 Morsella, E. 329 Mort, D.J. 118

Mortimer, A. 259 Morton, J. 319, 363 Moscovitch, M. 215, 228, 233 Müller-Lyer, F. 32, 33, 41, 62 Mulligan, N.W. 173 Murphy, D.R. 184 Murphy, G.L. 172 Murty, V.P. 379 Mustanski, B. 388 Muter, P. 140,141 Myles, K.M. 105 Na, D.L. 116 Naccache, L. 21 Nader, K. 191 Naeser, M.A. 348 Nairne, J.S. 151, 173 Naish, P. 51 Naka, M. 188 Nakamura, N. 35 Navarro, J. 66 Navon, D. 82 Neath, I. 151 Neely, J.H. 188 Neisser, U. 9–10, 28, 48, 84, 193, 196–197 Nekes, W. 69 Nelson, C.A. 195 Nelson, H.E. 283 Nelson, K. 195 Neufeld, J. 108 Newcombe, F. 362 Newell, A. 10, 94, 245 Newstead, S.E. 263 Nieuwenstein, M.R. 92 Nilssen, L. 66, 171 Nishihara, K. 30 Nixon, R.D.V. 373 Norman, D.A. 19, 29, 48, 73, 87–89, 293–294 Nowak, L.G. 47 Nunn, J.A., 106 Nyberg, L. 174 Nys, G.M. 233 O’Brien, D.P. 264 Oaksford, M. 268, 270, 395–396 Oatley, K. 390, 391 Oberauer, K. 140 Obleser, J. 354–355, 362 O’Carroll, R. 287 O’Connor, M. 215, 218 Ogden, J.A. 213, 214 Ohlsson, S. 249 Oldfield, S.R. 53 Olivers, C.N.L. 92 Ollinger, M. 250–251 O’Regan, J.K. 49

457

Ormerod, T.C. 248 O’Rourke, T.B. 320 O’Seaghdha, P.G. 328 Osherson, D. 286 Ost, J. 199 Otten, L.J. 168 Over, D.E. 263–264, 269, 271 Overman, A.A. 210 Owen, A.M. 153, 284, 288 Owen, D.H. 60 Ozonoff, S. 149 Oztekin, I. 154 Palmer, J.C. 198 Parker, S.P.A. 53 Parkin, A.J. 19, 167, 180–182, 184, 228, 233–234 Parra, M.A. 150 Parsons, L.M. 286 Pashler, H. 91, 185 Patterson, K.E. 318–319, 322–323, 352, 355, 362–363 Payton, T. 260 Pecher, C. 371–372 Pellegrino, G. 130 Perret, D. 80 Perret, E. 280 Persaud, N. 20 Peru, A. 125 Petersen, S.E. 79 Peterson, L.R. 140–141, 192 Peterson, M.J. 140–141, 192 Pham, M.T. 383, 385 Phillips, C.E. 148 Phillips, J.G. 94 Phillips, L. 210, 219 Pickering, M.J. 331 Picklesimer, M. 173 Pickrell, J.E. 199 Piercy, M.F. 180, 221–222, 227 Pillemer, D.B. 195 Pinker, S. 320–321, 334 Pisoni, D.B. 313 Plaut, D.C. 363–364 Poeppel, D. 53 Poletiek, F.H. 260 Polivy, J. 372 Poppel, E. 109 Posner, M. I. 78–79, 81, 90, 95 Postman, L. 159 Potter, M.C. 92 Potts, R. 190 Power, M.J. 191 Praamstra, P. 350 Price, C.J. 355, 359, 364 Prince, S.E. 179 Proffitt, D.R. 47 Pujol, M. 209, 213, 234

458

Author index

Raffone, A. 141 Raghunathan, R. 383, 385 Raine, A. 146 Ramachandran, V.S. 106–107 Ranganath, C. 180 Ranyard, R. 174 Rao, S.C. 46 Rasanen, M. 39 Rastle, K. 316 Ratner, K.G. 184 Ratner, N. 334 Rauschecker, J.P. 53 Raymond, J.E. 92 Rayner, K. 359–360 Read, J. 199, 232–233 Read, L. 81 Reason, J.T. 19, 88 Reed, J.M. 218 Reed, L.J. 216, 218 Reed, S.K. 248 Rees, G. 11, 21, 28 Reeve, D.K. 163 Regard, M. 231 Renault, B.S.131 Reverberi, C. 250, 285–286 Reyna, V.F. 270 Ribot, T. 211–212, 215 Riccio, G.E. 60 Richards, A. 383, 388, 397 Richmond, J. 195 Riddoch, M.J. 114, 120122, 124–125, 129–130 Rizzolatti, G. 116 Robbins, T.W. 148 Robertson, I.H. 117 Roca, M. 296, 298 Rock, I. 41 Roediger, H.L.III 192 Rogers, A. 233 Rogers, T.B. 167 Rose, D. 30 Rose, N.S. 168 Rosenbaum, R.S. 212, 224, 229–230 Rosenbloom, P.S. 94 Rosetti, Y. 118 Ross, E.D. 349, 351 Ross, G. 195 Rosselli, M. 300 Rossi, S. 260 Roth, H.L. 223, 345 Rouw, R. 106 Rubenstein, H. 316 Rubin, D.C. 158, 194, 196–197, 377 Rubin, E. 27 Rueckert, L. 279, 297 Rugg, M.D. 168 Ruggeri, M. 233

Rumelhart, D. E. 11, 30, 322–323 Russell, W.R. 231 Rusting, C.L. 375 Sabey, B. 37 Sacks, H. 330 Saffran, E.M. 363 Saffran, J. 311 Salame, P. 145 Saliba, A. 54 Saling, L.L. 94 Salmaso, D. 279 Salthouse, T.A. 234–235 Samuelson, H. 117 Sander, D. 379 Sarinopoulos, I. 384 Saunders, J. 200 Saunders, R.C. 216 Sayer, T.B. 67 Schachter, D.L. 179, 185, 192, 221, 226, 233, 235 Schaeken, W. 268 Schaffer, L.H. 91 Schank, R.C. 164 Scheerer, M. 244–245 Schenck T. 67 Schiller, D. 192 Schindler, B.A. 277 Schindler, I. 118 Schlesinger, I.M. 308 Schmida, M. 107 Schneider, G.E. 47, 112 Schneider, W. 17–18, 72–73, 93 Schnur, T.T. 347 Schott, B.H. 183 Schroyens, W. 262 Schul, Y. 391 Schulman, G.L. 72, 74, 79 Schulz, K.P. 149 Schunn, C.D. 160 Schwarz, N. 385 Scotko, B.G. 224 Scott, S.K. 53, 66, 303, 353 Scoville, W.B. 208, 214, 216, 226 Sedda, A. 54 Segall, M.H. 33, 35 Sehm, B. 215, 218 Seidenberg, M.S. 315–316, 319–320, 323 Selfridge, O.G. 10, 28– 29 Seligman, M.E.P. 20 Sellal, F. 215 Sergent, J. 130 Service, E. 146 Shaffer, L.H. 91 Shallice, T. 15, 19, 87–89, 124–125, 138, 144–145,

149, 233, 280, 285–287, 288, 290–291, 293–297, 339, 362–364 Shapiro, D. 263 Shapiro, K.L. 92 Shapley, R. 46 Shaw, J.S. 189 Shepard, R.N. 26–27, 30 Shepherd, E. 259 Sheppard, D.M. 117 Sheridan, J. 125 Shiffrin, R.M. 17–18, 73, 93, 137–138 Shimamura, A.P. 234 Shiv, B. 383–384 Shonk, K. 397 Shulman, H.G. 91 Siebert, M. 380 Siegal, M. 352 Sierra, M. 197 Signoret, J.L. 130 Simcock, G. 195 Simon, H.A. 163, 245, 248–249, 255 Simon, S.R. 132 Simons, J.S. 14, 223 Singh-Curry, V. 50 Skinner, B.F. 7, 309 Slobin, D.I. 310 Small, D.A. 387 Smilek, D. 104 Smith, C. 236 Smith, E.E. 153 Smith, M.L. 287 Smith, S.M. 174, 176 Snowling, M.J. 366–367, 369 Soechting, J.F. 61 Song, Z. 222 Soon, C.S. 21 Sorger, B. 128 Spears, R. 385 Spence, C. 62–63, 81, 107, 118 Sperber, D. 332 Sperling, G. 138 Spieler, D.H. 317 Spiers, H.J. 140, 223 Spitsyna, G. 364 Sprague, J.M. 118 Squeri, V. 61 Squire, L. 185, 213, 215, 218–219, 222, 225–229, 232 St. James, J.D. 85 St Jaques, P.L. 192 Standing, L. 175 Stanovich, K.E. 269 Starcke, K. 382 Starr, A. 210, 219 Staughton, G.C. 37 Stefanacci, L. 218

Author index Steinvorth, S. 212–214, 224–225, 227, 229 Sterkaj, F. 187, 190 Sternberg, R.J. 271 Steven, M.S. 102 Stevenson, R.J. 263 Stewart, F. 124–125 Stone, S.P. 113 Storandt, M. 149, 206, 210, 230 Storm, B.C. 188 Strawson, C. 315 Strayer, D.L. 92 Stroop, J.R. 18, 73, 104, 280, 294 Stuss, D.T. 149, 280, 297–298, 301 Styles, E.A. 97 Summala, H. 39 Summerfield, Q. 306 Suprenant, A.M. 151 Suslow, T. 379 Talarico, J.M. 196–197, 374 Talland, G.A. 209 Tandoh, K. 188 Tanenhaus, M.K. 325 Taylor, F.K. 184 Taylor, R. 287 Theeuwes, J. 38 Thomas, J.C. 247–248 Thomas, K. 388 Thomas, N.J.T. 49 Thompson, L.A. 176 Thompson, V.A. 270 Thomson, D.M. 171–172 Thomson, J.A. 385, 390 Thorndike, E.L. 186, 242 Tiedens, L.Z. 385, 397 Tipper, S.P. 77 Tippett, L.J. 130–131, 224, 283 Tisserand, D.J. 234 Toffalo, M.B.J. 176 Tomson, S.N. 104 Treadgold, L. 238 Treisman, A.M. 55, 75–76, 82–85 Troscianko, E. 176 Trueswell, J.C. 325 Tsuruhara, A. 42 Tuckey, M.R. 164 Tulving, E. 167, 169–173, 177–178, 181–183, 192, 194, 223–224, 376 Turner, G.R. 301 Turner, M.L. 151 Tweney, R.D. 260

Ucros, C.G. 376 Underwood, B.J. 159 Ungerleider, L.G. 46, 48, 72 Vallar, G. 114, 135, 139, 145–146 Vallée-Tourangeau, F. 260 Van der Linden, M. 153 Van Essen, D.C. 44 Van Leeuwen, T.M. 106 Varley, R.A. 352 Vela, E. 176 Velten, E. 372 Verfaillie, M. 223, 225 Verhaeghen, P. 234–235 Verschueren, N. 270 Victor, M. 216 Vitevitch, M.S. 313 Vlahovic, T.A. 333 Voeller, K.K.S. 117 Vroomen, J. 54, 312 Wada, Y. 130 Wagenaar, W.A. 194, 259 Wager, T. 153 Wagner, G.P. 287 Walker, B.N. 55 Wallraven, C. 61 Walter, B. 234 Ward, J. 100, 103–104, 108, 369, 393 Warner, M. 69 Warren, E.W. 232 Warren, J.E. 355 Warrington, E.K. 15, 124–125, 131, 138, 144–145, 178, 209, 220, 227, 362 Wason, P.C. 259, 263–264, 266 Waters, E.A. 384, 386, 388 Watson, D. 384 Watson, J.B. 6 Wearing, D. 140, 208, 210, 213, 218–219, 221, 227 Weaver, G.E. 167 Weeks, D. 232 Wegner, D.M. 21 Weinberg, J. 117 Weiner, B. 385 Weisberg, R.W. 244 Weisel, T.N. 11 Weiskrantz, L. 14, 20, 109, 111, 220, 227 Weiss, P.H. 106 Welford, A.T. 74, 91 Wells, G.L. 197 Welt, L. 275 Wenzel, A. 158

459

Wernicke, C. 14, 338–345, 347–348, 350, 352, 355, 358, 369 Wertheimer, M. 7, 27 Wessinger, C.M. 111 West, M.J. 216 West, R.F. 269 Westwood, D.A. 65, 67 Wetherick, N.E. 260 Whishaw, I.Q. 274 White, H.A. 188 White, S.H. 195 Whitlow, S.D. 221, 226 Whitney, P. 335 Whitty, C.W.M. 209 Wickelgren, W.A. 210–214 Wiesel, T.N. 28 Wilkins, A.J. 279 Williams, S.J. 199 Wilson, B.A. 140, 149–150, 208, 210, 213, 218–219, 221, 223, 227, 237–239 Wilson, C.E. 133 Wilson, D. 332 Wilson, M. 331 Wilson, T.P. 331 Winawer, J. 102 Wingate, M.E. 367 Winograd, E. 167 Wise, R.J. 357 Witthoft, N. 102 Wolters, G. 141, 197 Wood, B. 76 Wright, D.B. 198–199 Wundt, W. 6 Yakomoto, T. 130 Yantis, S. 54 Yaro, C. 108 Young, A.W. 126–127, 129, 132, 135, 361–362 Young, M.J. 372 Yu, J. 296 Zacher, W. 276 Zanetti, O. 237 Zangwill, O.L. 209 Zaragoza, M.S. 198 Zartorre, R.J. 90 Zeki, S. 49 Zevin, J. D. 315 Zhao, Z. 148 Zhu, B. 199 Zihl, J. 114, 361 Zola-Morgan, S. 222 Zwisterlood, P. 312

Subject index accent 304, 314, 352 action slips 18–19, 73, 88–89 affordances 45, 398 age of acquisition (AOA) 315, 317 agnosia 119–125 Alzheimer’s disease (AD) 149–150, 155, 205–208, 210, 213, 216, 223, 230, 234, 238 Ames room 33–35 amnesia 205–239; aetiology 205–208; anterograde 210– 218, 227, 231–232, 235, 238; concussion 231–232 ; declarative memory 219, 225–226, 229, 239; episodic and semantic 223–226; familiarity and context 221–223, 225–226, 229; implicit memory 211, 220–221, 225, 229, 234, 237, 239; in normal elderly 234–235; procedural and motor skills 219–220, 225–226; rehabilitation 236–238; retrograde 210–218, 223, 227, 229, 231–232, 235, 239 amnesia theories 226–229; encoding deficit theory 226–227; impaired binding 229–230; impaired declarative memory 229; impaired perceptual processing 230; multiple trace theory 228–229; retrieval deficit theory 227; standard model of consolidation 228 amygdala 374, 379–380, 383–384; and long-term memory 379, 380; and perception 379 analogical mapping 252–253, 256 anechoic chamber 53 anger 385–387 anterograde amnesia (AA) 210– 218, 227, 231–232, 235, 238 anxiety 37, 374, 381–384; and decision making, 382–384;

and future orientation 381–382 aperceptive agnosia 119–120 aphasia 337–351; Broca’s 337–339, 341, 343, 346–349, 351–352, 357–358; conduction 339, 341–342, 344, 348, 355; global 338, 341, 348; Wernicke’s 338– 345, 347–348, 350, 352, 355, 358; Wernicke-Lichtheim model 339–345, 348 articulatory control process 144–145, 153 articulatory suppression 144–146 associative agnosia 119–120 attention 70–97, 114–118, 372–374; and anxiety 373; auditory 55–56, 74–77, 81, 90–91; bottleneck 74; capacity theory 86; capture 71; control 73, 87–89, 93–94; divided 90–91; early selection 75, 86; late selection 76; and memory 373; spotlight 78; visual 77–80 attentional narrowing 372, 373 attenuation theory 76 auditory attention 55–56, 74–77, 81, 90–91 auditory localisation 51, 52, 53, 54 autism 20, 149, 337, 368 autobiographical memory 159, 177, 193–196, 212–213, 374, 375 automatic processing 17–19, 94, 149, 180, 185, 190, 219, 221, 229, 234 behaviourism 6–7, 242 binaural cues 51, 398 binding problem 72, 83 blindsight 20, 109–113, 116 blindspot 99–100 Boston Aphasia Classification System 341–342, 348 bottom-up processing 9, 28, 31–32, 34, 36–38, 41, 44, 54, 56, 62, 66, 73–74, 79, 89, 398, 406

breakthrough of unattended signal 75–76 Brixton Spatial Anticipation Test 285–286, 297 Broca’s Aphasia 337–339, 341, 343, 346–349, 351–352, 357–358 Broca’s area 13–14, 153, 274, 338, 343, 346–349, 351, 357–358 category-specific agnosia 125 cell assembly 16 central executive 14, 19, 143, 149–150, 153–154, 191, 210, 230, 233, 235, 294, 298 change blindness 50 chunking 165 cognitive estimation 286–287 cognitive interview 176, 200–202 cognitive load 12,87,95,269 cognitive neuropsychology 5, 12, 22 cognitive neuroscience 4–5, 12, 23 cognitive psychology (definition) 3 colour perception 106–107 computer modelling 4–5, 10–11, 22 concept formation 286 concussion 231–232 conduction aphasia 339, 341–342, 344, 348, 355 confabulation 209, 233–234 confirmation bias 259–261, 264 connectionist models 30, 132, 319–320, 323, 328, 363–364 consciousness 19–22, 23, 137–140, 149–150, 152, 166, 178, 207, 219–221, 223, 225–226, 229, 233–234, 237 conspicuity, attention 38–39, 398, 405 conspicuity, sensory 37–39, 398, 405 contention scheduling 294, 295 context-dependent memory 173–176, 200 controlled processing 17–19

Subject index conversational plagiarism 184 Corsi blocks 147 covert recognition 131, 132,134 cryptomnesia 184 decay with disuse 160, 186, 189 deductive reasoning see reasoning déjà vu 184 depression 177, 190–192, 197, 208, 232–233 digit span 139, 141–144, 146–147 direct perception 45 directed forgetting 190–191 disinhibition 108, 284, 296 dorsal stream 46–50, 53, 63–64, 67–68, 72, 123–124, 132, 153, 400 double dissociation 15, 139 dysexecutive syndrome 149, 155, 278, 293 dyslexia 358–367; phonological 362; deep 362–364 Ebbinghaus illusion 63–64 ecological validity 192–193, 371 effortful processing 180, 185, 190–191 elaborative encoding 168–170, 173 electroconvulsive therapy (ECT) 208, 232–233 electroencephalography (EEG) 105–106 encoding specificity principle (ESP) 171–174, 176, 376, 377 episodic buffer 150, 154 episodic memory 212, 215, 217, 223–226, 229 errorless learning 237 executive functions 273, 278, 287, 293 extended hippocampal system 216 external memory 49, 236–237 eyewitness testimony 189, 197–200 face recognition 126–127, 130, 132, 167 face specificity in prosopagnosia 129–131 facial speech analysis 126 false memories 199 familiarity 171, 179–181, 184–185, 207, 209, 214, 217, 221–223, 225–226, 229

feature extraction 10–11, 27–30, 32, 403 feature integration theory 83–85; conjunction search 83, 84; feature search 83, 84 feature overlap 172–173, 176, 178 filter model of attention 75 flanker 64, 65 flashbulb memory 193, 196–197, 377 forgetting curve 158–160 form agnosia 120–125 fragmented words 220 frontal lobes 13–14, 19, 53, 73, 89–90, 108, 118, 149, 153, 212, 216–218, 221, 233–234, 273–300; anatomy and physiology 274–275; early clinical studies 275–276; early animal studies 276–277; fractionation of executive functions 296–298; frontal lobe syndrome 278; later clinical studies 277–278; and memory disorder 213, 216–217, 221, 233–234 functional fixedness 243–244 functional magnetic resonance imaging (fMRI) 105–108 fusiform face area (FFA) 87, 129, 132 fusiform gyrus 107, 129, 133, 183 galvanic skin response (GSR) 76 general problem solver 245, 246 generate and recognise (GR) theory 171 geons 28, 30, 401 Gestalt psychology 7–8, 27–29, 35, 38, 55, 242–244, 249, 251, 401 global aphasia 338, 341, 348 global–local distinction 82 goal-oriented problem solving 288–289 haptic perception 58–63, 65–68, 114, 401, 404 Hayling Sentence Completion Test 280, 297 Hermann grid 32 Herpes Simplex Encephalitis (HSE) 206, 208, 210, 213–219, 221, 223, 225, 227 heuristics 245 hippocampus 215–216, 224–225, 228–230, 238

461

hobbits and orcs problem 246, 247, 248, 289 hypothesis testing, perceptual 41–44 illusions, haptic 62, 65 illusions, visual 6, 31, 33, 35, 44–45, 47–48, 62–63, 65, 100 impasse 249 implicit memory 211, 220–221, 225, 229, 234, 237, 239 individuation 130 inductive reasoning see reasoning infantile amnesia 195 inner scribe 148 insight 243, 249 interoceptor 59–60 introspective report 242 intuition 184 irrelevant speech effect 145 judgement and decision making 380–393; and anger 385–387; and anxiety 381–384; and cognitive neuroscience 391–395; and positive mood 387–389; and sad mood 384–385 kinesthesis 60–62, 65 Korsakoff’s syndrome 206, 208–210, 212–213, 216, 220–223, 227–228, 234, 238 language 303–335 language disorders 336–369 levels of processing (LOP) 166–169, 174 lexical decision task 311, 314–317, 320, 329, 363 linguistics 309–311 lip-reading 81, 126 listened but failed to hear 58 logogens 319–320 long-term memory 156–203 long-term potentiation (LTP) 17 looked but failed to see (LBFS) 37, 58 magnocellular pathway 46 Marr’s computational theory 29 mask, visual 43–44, 77, 104, 406 matchstick problems 250–251, 283 McGurk effect 54

462

Subject index

means–ends analysis 246 memory (long–term) 156–203; context reinstatement 175–176, 200–201; decay 159–160; distortion 161, 164–165, episodic 177–179, 185, 212, 215, 217, 223–226, 229; explicit 181–185; implicit 181–185; interference 159–160, 188, 192, 194; retrieval cues 170–176, 193–194, 201; semantic 177–179, 185, 212, 215, 223–226, 229; misinformation effect 192 memory (short-term) 137–142, 154; capacity 141–142; duration 140–141 mental models see reasoning mental set 244 mirages 32 mnemonics 165, 237 mood congruity 375, 376 mood states 371–397; and everyday life 371 mood-state-dependent memory 176–177, 376, 377 moral dilemmas 392–395; and dorsolateral prefrontal cortex 392–394; and utilitarian judgements 392–394; and ventromedial prefrontal cortex 392–394 morphemes 304, 307, 312, 316, 320–321, 326–328 Magnetic Resonance Imaging (MRI) 5 Müller-Lyer illusion 32–33, 35, 41, 44, 62–63 Multiple Errands Test 290, 292, 297 music 55, 58, 66, 100, 102, 124–125, 165, 174, 217, 219, 351, 366, 371–372, 375, 387 negative priming 77–78 neural networks 17, 30–31, 35, 403 neuron 15–16 Neuropage 238 neurorealism 106 neurotransmitter 15 new theory of disuse (NTD) 160, 186, 189 nine-dot problem 245 nociception 60 nonsense syllable 158, 160 numena 37, 403

object selection 77 optimistic bias 382, 386–388 orienting task 166–167, 173, 181 Pandemonium 28, 29, 403 parallel distributed processing (PDP) 30, 316, 323, 403 parvocellular pathway 46 perseveration 116, 149, 282, 283–284, 285, 295 Positron Emission Tomography (PET) 5 Phineas Gage 275–276 phobias 189–190, 197 phonemes 304–305, 307, 313, 319, 326, 328, 350, 354–357, 362–363, 367 phonological loop 139, 143–148, 150, 153–154 phonological store 144–145, 153–154 pitch, auditory 305, 353, 367–368 post-traumatic stress disorder (PTSD) 184, 189, 192, 197 pragmatic reasoning schemata see reasoning pragmatics 304, 309, 331 problem-solving 257–270; gestalt approach 242–245, 249; expertise 255; analogy 251–257; information processing approach 245–249; stages 245; strategies 245–249; problem reduction 246; problem representation 249–251 problem-solving and reasoning deficits and the frontal lobes 279–293; deficits in everyday higher order planning 289–293; impairments in abstract and conceptual thinking 281– 286; impairments in the deployment of attention 279–281; impaired strategy formation 286–289 procedural knowledge 95–96 procedural memory 219–220, 225–226 proprioception 59–62, 65–66, 404 prosopagnosia 126–134; congenital 126, 133–134; developmental 126–133 Proust phenomenon 176

psychogenic amnesia 205–206, 215, 231, 235–236 psychological refractory period 74, 91 pure word deafness 349–350 raster displays 110 reading 358–364, 366–367 reasoning 257–270, 395–396; deductive 261–264; and depression 395–396; dual process accounts 269–270; inductive 258–261; mental logic theories 264–265; mental models 266–268; and positive mood 396; pragmatic reasoning schemata 265–266; probabilistic approach 268; and working memory 395–396 recency effect 139–140 recognition and recall 170–171 recollection 179–180, 185 reconsolidation 191–192 recovered memories 199, 377–379; and repression 379; and therapist 378 rehabilitation 114–118, 224, 236–238 remember and know (R & K) procedure 181, 223, 234 reminiscence bump 194–195 retrieval-induced forgetting (RIF) 160, 187–190, 200 retrograde amnesia (RA) 210–218, 223, 227, 229, 231–232, 235, 239 reversible figure 27, 404 Ribot’s law 211, 212–213 rules of inference 262 sadness 375–376, 384–385; and decision making 384,385; and past orientation 381, 382 schadenfreude 385 schema 7–9, 11, 22, 25–26, 31, 88–89, 160–162, 164, 166, 182, 195, 253, 256–257, 265–266, 271, 293–295, 399, 403–406 schema-driven processing 9 scotoma 109–112 scripts 164 selective attention 12 semantic memory 211–213, 217, 223–226, 229 SenseCam 238 shadowing 74–75

Subject index shadowing, sound 51 short-term memory 137–142, 154; capacity 141–142; duration 140–141; working memory 86–87, 142–154 short-term memory impairment 208–210, 230 sign language 306–307 Six Element Test 290 size constancy 33, 34, 405 size-contrast 63–65 spatial neglect 113–119 spectral cues 51, 405 speech production 326–329 state-action tree 246 state-dependent memory 176–177 stimulus-driven processing 9 striate cortex 109–113 Stroop task 18, 73–74, 104–105, 108, 168, 280, 290 subliminal priming 76 sunk-cost effect 386 supervisory attention system 19, 293–295 synaesthesia 100–109 synapse 15–16 syntax 303–304, 306, 310, 321, 326, 333

temporal lobes 13–14, 118, 123, 127, 129, 206, 208, 210–211, 214–215, 217–219, 223–224, 228–229, 233 testing effect 185–186, 192, 194 theory of mind 20 top-down processing 9, 23, 31–38, 41, 44–45, 54, 56, 62, 73–74, 78–79, 89, 280, 300, 399, 406 touch, sense of 58–62, 65, 80 Tourette syndrome 149 tower of Hanoi problem 247 Tower of Hanoi task 288–289 Tower of London task 288 transcranial magnetic stimulation (TMS) 50, 90, 106, 406 transfer-appropriate processing 173–174 tumour problem 253 two-string problem 243

template 25–28, 30–31, 49, 404, 405 temporal lobe surgery 208, 210, 213–214

ventral stream 46–50, 53, 68, 123–124, 132, 153, 406 ventriloquist effect 81 verbal fluency test 280

Urbach-Wiethe disease 380 utilisation behaviour 295

463

visual acuity 43, 49, 61, 119, 126, 404 visual cache 148, 153 visual field 109–112, 114–116 visual form agnosia 120–125 visual integrative agnosia 120–125 visual pathways 113 visuo-spatial sketchpad 143, 146–148, 150, 154 Wason’s four-card selection task 263–264 water jug problem 244 weapon focus 374 Wernicke’s aphasia 13–14, 338–345, 347–348, 350, 352, 355, 358 Wernicke–Lichtheim model of aphasia 339–345, 348 what? pathway 46, 48, 72, 77, 123, 153 where? pathway 46, 48, 72, 77, 53, 123, 153 Williams syndrome 148 Wisconsin Card Sorting Test 282, 283, 284, 297 word-length effect 144–145, 356 working memory (WM) 86–87, 142–154; and attention 86–87; individual differences 151–152; neuro-imaging 153–154

This page intentionally left blank

Taylor & Francis

eBooks

ORDER Y FREE 3 OUR 0 DAY INSTITU TIONA L TRIAL T ODAY!

FOR LIBRARIES

Over 22,000 eBook titles in the Humanities, Social Sciences, STM and Law from some of the world’s leading imprints. Choose from a range of subject packages or create your own! Free MARC records Benefits for

you

COUNTER-compliant usage statistics Flexible purchase and pricing options Off-site, anytime access via Athens or referring URL

Benefits for your

user

Print or copy pages or chapters Full content search Bookmark, highlight and annotate text Access to thousands of pages of quality research at the click of a button

For more information, pricing enquiries or to order a free trial, contact your local online sales team. UK and Rest of World: [email protected] US, Canada and Latin America: [email protected]

www.ebooksubscriptions.com

eBooks

A flexible and dynamic resource for teaching, learning and research.